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| Rank,ID,Title,Authors,Year,Venue,Track,Status,Primary Area,Keywords,Citations,BM25 Score,Combined Score,DOI,URL,PDF,Source,TLDR,Abstract | |
| 1,,Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification,Cui-Na Jiao; Ying-Lian Gao; Na Yu; Jin-Xing Liu; Lianyong Qi,2020,IEEE journal of biomedical and health informatics,,,,,46,0.000,0.137,10.1109/JBHI.2020.2975199,https://www.semanticscholar.org/paper/f68b6e6c27a63f965cd6612cfd67acf1b40d3b5b,,semantic_scholar,,"Non-negative Matrix Factorization (NMF) is a dimensionality reduction approach for learning a parts-based and linear representation of non-negative data. It has attracted more attention because of that. In practice, NMF not only neglects the manifold structure of data samples, but also overlooks the" | |
| 2,,Ground states for the planar NLSE with a point defect as minimizers of the constrained energy,R. Adami; F. Boni; R. Carlone; L. Tentarelli,2021,Calculus of Variations and Partial Differential Equations,,,,,32,0.000,0.120,10.1007/s00526-022-02310-8,https://www.semanticscholar.org/paper/a25875f86614ddf77564ca2f0be903da9dd8d583,,semantic_scholar,,"We investigate the ground states for the focusing, subcritical nonlinear Schrödinger equation with a point defect in dimension two, defined as the minimizers of the energy functional at fixed mass. We prove that ground states exist for every positive mass and show a logarithmic singularity at the de" | |
| 3,,An Ode to an ODE,K. Choromanski; Jared Davis; Valerii Likhosherstov; Xingyou Song; J. Slotine,2020,arXiv.org,,,,,32,0.000,0.100,,https://www.semanticscholar.org/paper/77774a7a123460ad58faee490d4751e8f17a7a58,,semantic_scholar,,"We present a new paradigm for Neural ODE algorithms, called ODEtoODE, where time-dependent parameters of the main flow evolve according to a matrix flow on the orthogonal group O(d). This nested system of two flows, where the parameter-flow is constrained to lie on the compact manifold, provides sta" | |
| 4,,Hyperbolic compactification of M-theory and de Sitter quantum gravity,G. Luca; E. Silverstein; G. Torroba,2021,SciPost Physics,,,,,30,0.000,0.124,10.21468/SciPostPhys.12.3.083,https://www.semanticscholar.org/paper/c389bba45638af1d627520ccaa3bf0ef217fe2cd,https://scipost.org/10.21468/SciPostPhys.12.3.083/pdf,semantic_scholar,,"We present a mechanism for accelerated expansion of the universe in the generic case of negative-curvature compactifications of M-theory, with minimal ingredients. M-theory on a hyperbolic manifold with small closed geodesics supporting Casimir energy -- along with a single classical source (7-form " | |
| 5,,The non-adiabatic nanoreactor: towards the automated discovery of photochemistry†,Elisa Pieri; Dean Lahana; Alexander M Chang; Cody R Aldaz; K. Thompson,2021,Chemical Science,,,,,24,0.000,0.126,10.1039/d1sc00775k,https://www.semanticscholar.org/paper/5968f7fd9a1e57e9fc713d17a02013297599a842,https://pubs.rsc.org/en/content/articlepdf/2021/sc/d1sc00775k,semantic_scholar,,"The ab initio nanoreactor has previously been introduced to automate reaction discovery for ground state chemistry. In this work, we present the nonadiabatic nanoreactor, an analogous framework for excited state reaction discovery. We automate the study of nonadiabatic decay mechanisms of molecules " | |
| 6,,MoDANet: Multi-Task Deep Network for Joint Automatic Modulation Classification and Direction of Arrival Estimation,Van-Sang Doan; Thien Huynh-The; Van-Phuc Hoang; Duy T. Nguyen,2022,IEEE Communications Letters,,,,,22,0.000,0.138,10.1109/lcomm.2021.3132018,https://www.semanticscholar.org/paper/816c248b74fbd8db43a85747dde57beedab2dbaf,,semantic_scholar,,"In this letter, a multi-task deep convolutional neural network, namely MoDANet, is proposed to perform modulation classification and DOA estimation simultaneously. In particular, the network architecture is designed with multiple residual modules, which tackle the vanishing gradient problem. The mul" | |
| 7,,SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization,Songtao Lu,2023,Neural Information Processing Systems,,,,,19,0.000,0.161,,https://www.semanticscholar.org/paper/245e67d4acd761b1d5b82bd5279803a48831c1bf,,semantic_scholar,, | |
| 8,,ProxNLP: a primal-dual augmented Lagrangian solver for nonlinear programming in Robotics and beyond,Wilson Jallet; Antoine Bambade; N. Mansard; Justin Carpentier,2022,arXiv.org,,,,,18,0.000,0.148,10.48550/arXiv.2210.02109,https://www.semanticscholar.org/paper/9a59529464edf5dc477afd2dcce76b892b2964f1,http://arxiv.org/pdf/2210.02109,semantic_scholar,,"Mathematical optimization is the workhorse behind several aspects of modern robotics and control. In these applications, the focus is on constrained optimization, and the ability to work on manifolds (such as the classical matrix Lie groups), along with a specific requirement for robustness and spee" | |
| 9,,Using Principal Paths to Walk Through Music and Visual Art Style Spaces Induced by Convolutional Neural Networks,E. Gardini; M. Ferrarotti; A. Cavalli; S. Decherchi,2021,Cognitive Computation,,,,,16,0.000,0.119,10.1007/s12559-021-09823-y,https://www.semanticscholar.org/paper/7896c2c5e0a1734b4c69c73aeccca136f09ea433,https://link.springer.com/content/pdf/10.1007/s12559-021-09823-y.pdf,semantic_scholar,,"Computational intelligence, particularly deep learning, offers powerful tools for discriminating and generating samples such as images. Deep learning methods have been used in different artistic contexts for neural style transfer, artistic style recognition, and musical genre recognition. Using a co" | |
| 10,,Hilbert Bundles and Holographic Space–Time Models,T. Banks,2023,Astronomy,,,,,14,0.000,0.149,10.3390/astronomy4020007,https://www.semanticscholar.org/paper/671aba98f173bf3108668e4bf136331796a00171,,semantic_scholar,,"We reformulate holographic space–time models in terms of Hilbert bundles over the space of the time-like geodesics in a Lorentzian manifold. This reformulation resolves the issue of the action of non-compact isometry groups on finite-dimensional Hilbert spaces. Following Jacobson, I view the backgro" | |
| 11,,Asymptotic profiles for a nonlinear Schrödinger equation with critical combined powers nonlinearity,Shiwang Ma; Vitaly Moroz,2023,Mathematische Zeitschrift,,,,,11,0.000,0.149,10.1007/s00209-023-03271-0,https://www.semanticscholar.org/paper/9b75f0de537b0eb389208a43392d8fe2424a38cf,https://link.springer.com/content/pdf/10.1007/s00209-023-03271-0.pdf,semantic_scholar,,"We study asymptotic behaviour of positive ground state solutions of the nonlinear Schrödinger equation $$\begin{aligned} -\Delta u+u=u^{2^*-1}+\lambda u^{q-1} \quad \textrm{in}\, {\mathbb {R}}^N,\qquad \qquad \qquad \qquad \qquad {(P_\lambda )} \end{aligned}$$ - Δ u + u = u 2 ∗ - 1 + λ u q - 1 in R " | |
| 12,,Nonholonomic and constrained variational mechanics,A. D. Lewis,2020,,,,,,10,0.000,0.091,10.3934/jgm.2020013,https://www.semanticscholar.org/paper/69a2d7a0fccd5b709fe2aeedfad1e303adec446d,https://www.aimsciences.org/article/exportPdf?id=6438a283-c843-455a-9966-141eb920f0c5,semantic_scholar,,"Equations governing mechanical systems with nonholonomic constraints can be developed in two ways: (1) using the physical principles of Newtonian mechanics; (2) using a constrained variational principle. Generally, the two sets of resulting equations are not equivalent. While mechanics arises from t" | |
| 13,,The Heterotic-Ricci Flow and Its Three-Dimensional Solitons,Andrei Moroianu; And ´ANGEL J. MURCIA; C. Shahbazi; F. Mathematik,2023,Journal of Geometric Analysis,,,,,9,0.000,0.145,10.1007/s12220-024-01570-4,https://www.semanticscholar.org/paper/7a71933db091ad5805894c8d8d870fc463ff20c6,https://link.springer.com/content/pdf/10.1007/s12220-024-01570-4.pdf,semantic_scholar,,"We introduce a novel curvature flow, the Heterotic-Ricci flow, as the two-loop renormalization group flow of the Heterotic string common sector and study its three-dimensional compact solitons. The Heterotic-Ricci flow is a coupled curvature evolution flow, depending on a non-negative real parameter" | |
| 14,,Curvature of quaternionic Kähler manifolds with $$S^1$$-symmetry,V. Cort'es; A. Saha; D. Thung,2020,Manuscripta mathematica,,,,,9,0.000,0.116,10.1007/S00229-021-01294-7,https://www.semanticscholar.org/paper/08656e15d80659e26bece795a56760ad9794c44e,https://link.springer.com/content/pdf/10.1007/s00229-021-01294-7.pdf,semantic_scholar,,"We study the behavior of connections and curvature under the HK/QK correspondence, proving simple formulae expressing the Levi-Civita connection and Riemann curvature tensor on the quaternionic Kähler side in terms of the initial hyper-Kähler data. Our curvature formula refines a well-known decompos" | |
| 15,,Hypercomplex Almost Abelian Solvmanifolds,A. Andrada; M. L. Barberis,2022,Journal of Geometric Analysis,,,,,8,0.000,0.149,10.1007/s12220-023-01277-y,https://www.semanticscholar.org/paper/df98f8490831b16a07194551aabea4aa51a01b5a,,semantic_scholar,,We give a characterization of almost abelian Lie groups carrying left invariant hypercomplex structures and we show that the corresponding Obata connection is always flat. We determine when such Lie groups admit HKT metrics and study the corresponding Bismut connection. We obtain the classification | |
| 16,,Rolling Against a Sphere The Non-transitive Case,Y. Chitour; M. Godoy; Molina Petri Kokkonen; I. Markina,2020,,,,,,8,0.000,0.083,,https://www.semanticscholar.org/paper/ff0891b332cad2eeadef90ad57e3eae4ea82dbad,,semantic_scholar,, | |
| 17,,Cortico-Cerebellar Hyper-Connections and Reduced Purkinje Cells Behind Abnormal Eyeblink Conditioning in a Computational Model of Autism Spectrum Disorder,Emiliano Trimarco; Pierandrea Mirino; Daniele Caligiore,2021,Frontiers in Systems Neuroscience,,,,,7,0.000,0.137,10.3389/fnsys.2021.666649,https://www.semanticscholar.org/paper/105dfc9dd495e4e279cc08f6ae88cfa481806c1f,https://doi.org/10.3389/fnsys.2021.666649,semantic_scholar,,Empirical evidence suggests that children with autism spectrum disorder (ASD) show abnormal behavior during delay eyeblink conditioning. They show a higher conditioned response learning rate and earlier peak latency of the conditioned response signal. The neuronal mechanisms underlying this autistic | |
| 18,,Revealing the hidden structure of disordered materials by parameterizing their local structural manifold,Thomas J. Hardin; Michael Chandross; Rahul Meena; Spencer Fajardo; Dimitris G. Giovanis,2024,Nature Communications,,,,,6,0.000,0.171,10.1038/s41467-024-48449-0,https://www.semanticscholar.org/paper/7ddf9876b5e857d2fbbb010238501dd51550e605,https://www.nature.com/articles/s41467-024-48449-0.pdf,semantic_scholar,,"Durable interest in developing a framework for the detailed structure of glassy materials has produced numerous structural descriptors that trade off between general applicability and interpretability. However, none approach the combination of simplicity and wide-ranging predictive power of the latt" | |
| 19,,Manifold learning for fMRI time-varying functional connectivity,J. Gonzalez-Castillo; Isabel S. Fernandez; K. Lam; D. Handwerker; Francisco Pereira,2023,Frontiers in Human Neuroscience,,,,,6,0.000,0.162,10.3389/fnhum.2023.1134012,https://www.semanticscholar.org/paper/71ae44f01b9201f94779f59aace871f720a77c6d,https://www.frontiersin.org/articles/10.3389/fnhum.2023.1134012/pdf,semantic_scholar,,"Whole-brain functional connectivity (FC) measured with functional MRI (fMRI) evolves over time in meaningful ways at temporal scales going from years (e.g., development) to seconds [e.g., within-scan time-varying FC (tvFC)]. Yet, our ability to explore tvFC is severely constrained by its large dimen" | |
| 20,,Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons,Qianyi Li; Cengiz Pehlevan,2020,Neural Information Processing Systems,,,,,6,0.000,0.087,,https://www.semanticscholar.org/paper/3332fe63e6088e0ac173d9c259b521ca9c72e39b,,semantic_scholar,,"Excitation-inhibition (E-I) balance is ubiquitously observed in the cortex. Recent studies suggest an intriguing link between balance on fast timescales, tight balance, and efficient information coding with spikes. We further this connection by taking a principled approach to optimal balanced networ" | |
| 21,,Hyper-holomorphic connections on vector bundles on hyper-Kähler manifolds,Francesco Meazzini; Claudio Onorati,2022,Mathematische Zeitschrift,,,,,5,0.000,0.217,10.1007/s00209-022-03176-4,https://www.semanticscholar.org/paper/23584ba7780c416c7064971241be0e1b4fcb2cae,,semantic_scholar,,"We study infinitesimal deformations of autodual and hyper-holomorphic connections on complex vector bundles on hyper-Kähler manifolds of arbitrary dimension. In particular, we describe the DG Lie algebra controlling this deformation problem. Moreover, we prove associative formality for derived endom" | |
| 22,,"Quantum Substrate Dynamics (QSD): A Relativistic Field Model of Emergent Mass, Inertia and Gravity",Michael Bush,2025,Preprints.org,,,,,5,0.000,0.182,10.20944/preprints202506.0988.v2,https://openalex.org/W4411392906,https://www.preprints.org/frontend/manuscript/724c52c071a67c93de9b5da3679bd484/download_pub,openalex,,"Quantum Substrate Dynamics (QSD) is a Lorentz-invariant, coherence-based field theory in which mass, gravity, and inertia emerge from phase-stable excitations within a conserved physical substrate. In this framework, mass appears as a coherence-locked phase lattice, inertia arises from reconfigurati" | |
| 23,,New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm,Saniye Maihemuti; Weiqing Wang; Jiahui Wu; Haiyun Wang; Muladi Muhedaner,2022,Energies,,,,,5,0.000,0.129,10.3390/en15249655,https://www.semanticscholar.org/paper/cbe9f8f251bdd41cc74af75452f80d37df070fad,https://www.mdpi.com/1996-1073/15/24/9655/pdf?version=1671672501,semantic_scholar,,"With the rapid expansion of new energy in China, the large-scale grid connection of new energy is increasing, and the operating safety of the new energy power system is being put to the test. The static security and stability region (SSSR) with hyper-plane expression is an effective instrument for s" | |
| 24,,MODES: model-based optimization on distributed embedded systems,Junjie Shi; Jiang Bian; Jakob Richter; Kuan-Hsun Chen; J. Rahnenführer,2021,Machine-mediated learning,,,,,5,0.000,0.111,10.1007/s10994-021-06014-6,https://www.semanticscholar.org/paper/039810d9407974cad6c0c303bc5967c4ae8ae108,https://link.springer.com/content/pdf/10.1007/s10994-021-06014-6.pdf,semantic_scholar,,"The predictive performance of a machine learning model highly depends on the corresponding hyper-parameter setting. Hence, hyper-parameter tuning is often indispensable. Normally such tuning requires the dedicated machine learning model to be trained and evaluated on centralized data to obtain a per" | |
| 25,,On Ricci curvature of submanifolds in statistical manifolds of constant (quasi-constant) curvature,A. Siddiqui; M. Shahid; Jae Won Lee,2020,,,,,,5,0.000,0.104,10.3934/math.2020227,https://www.semanticscholar.org/paper/9c310b3f6d58403c66d76f3e5456a9a811d1df7c,https://doi.org/10.3934/math.2020227,semantic_scholar,,"In 1999, B. Y. Chen established a sharp inequality between the Ricci curvature and the squared mean curvature for an arbitrary Riemannian submanifold of a real space form. This inequality was extended in 2015 by M. E. Aydin et al. to the case of statistical submanifolds in a statistical manifold of " | |
| 26,,"No Minima, No Collisions: Combining Modulation and Control Barrier Function Strategies for Feasible Dynamical Collision Avoidance",Yifan Xue; Nadia Figueroa,2025,arXiv.org,,,,,4,0.000,0.192,10.48550/arXiv.2502.14238,https://www.semanticscholar.org/paper/9e252f402a62a45d310efe1391f85e19133e425a,,semantic_scholar,,"As prominent real-time safety-critical reactive control techniques, Control Barrier Function Quadratic Programs (CBF-QPs) work for control affine systems in general but result in local minima in the generated trajectories and consequently cannot ensure convergence to the goals. Contrarily, Modulatio" | |
| 27,,Nonlinear Cauchy Elasticity,Arash Yavari; Alain Goriely,2025,Archive for Rational Mechanics and Analysis,,,,,4,0.000,0.185,10.1007/s00205-025-02120-0,https://openalex.org/W4413891066,https://link.springer.com/content/pdf/10.1007/s00205-025-02120-0.pdf,openalex,,"Abstract Most theories and applications of elasticity rely on an energy function that depends on the strains from which the stresses can be derived. This is the traditional setting of Green elasticity, also known as hyper-elasticity. However, in its original form the theory of elasticity does not as" | |
| 28,,"Mock Modularity at Work, or Black Holes in a Forest",Sergei Alexandrov,2025,Entropy,,,,,3,0.000,0.181,10.3390/e27070719,https://openalex.org/W4411972976,https://www.mdpi.com/1099-4300/27/7/719/pdf?version=1751469528,openalex,,"Mock modular forms, first invented by Ramanujan, provide a beautiful generalization of the usual modular forms. In recent years, it was found that they capture the generating functions of the number of microstates of BPS black holes appearing in compactifications of string theory with 8 and 16 super" | |
| 29,,Estimating Functional Brain Networks by Low-Rank Representation With Local Constraint,Zhigang Li; Weimin Zheng; Honghong Liu; Jingyu Liu; Chang Yan,2024,IEEE transactions on neural systems and rehabilitation engineering,,,,,3,0.000,0.173,10.1109/TNSRE.2024.3355769,https://www.semanticscholar.org/paper/8f0d342861da43a0c039cbb16c33bfab55b54d5b,https://ieeexplore.ieee.org/ielx7/7333/4359219/10403846.pdf,semantic_scholar,,"The functional architecture undergoes alterations during the preclinical phase of Alzheimer’s disease. Consequently, the primary research focus has shifted towards identifying Alzheimer’s disease and its early stages by constructing a functional connectivity network based on resting-state fMRI data." | |
| 30,,Clarke Transform and Clarke Coordinates - A New Kid on the Block for State Representation of Continuum Robots,R. Grassmann; J. Burgner-Kahrs,2024,arXiv.org,,,,,3,0.000,0.167,10.48550/arXiv.2409.13826,https://www.semanticscholar.org/paper/b085d64d385554afe5b567875494a232cb6f9f9f,,semantic_scholar,,"For almost all tendon-driven continuum robots, a segment is actuated by three or four tendons constrained by its mechanical design. For both cases, methods to account for the constraints are known. However, for an arbitrary number of tendons, a disentanglement method has yet to be formulated. Motiva" | |
| 31,,A Lightweight Certificateless Signcryption Scheme based on HCC for securing Underwater Wireless Sensor Networks (UWSNs),Meenakshi Gupta; Poonam Gera; Bharavi Mishra,2023,International Conference on Security of Information and Networks,,,,,3,0.000,0.159,10.1109/SIN60469.2023.10474770,https://www.semanticscholar.org/paper/8dfa770c6dfc24568c6ae831e0e133a97b3c0c25,,semantic_scholar,,Underwater Wireless Sensor Networks (UWSNs) consist of sensor nodes deployed within bodies of water. Wireless connections and the harsh underwater environment make sensors susceptible to a variety of malevolent attacks and security concerns. The fundamental concern of the UWSN is secure and reliable | |
| 32,,Transcending Time (Feels),Jose M. Garza,2021,,,,,,3,0.000,0.105,10.30535/MTO.27.1.3,https://www.semanticscholar.org/paper/7b99ae8e00fb097955958a3e584bf4d58bc3dcaa,https://mtosmt.org/issues/mto.21.27.1/mto.21.27.1.garza.pdf,semantic_scholar,,"Over the past fifteen years, much of the music-theoretical scholarship on heavy metal has addressed metric processes (Lucas 2019, Capuzzo 2018, Hannan 2018, Lucas 2018, Lennard 2016, Smialek 2008, Pieslak 2007) and the use of the voice (Smialek 2017, Young 2018). A significant portion of the literat" | |
| 33,,Cognitive Computing Continuum: State-of-the-Art Review and ENACT Vision & Approach,Ioanna Angeliki Kapetanidou; Alexandros Nizamis; Efstathios Karanastasis; Gabriel-Mihail Danciu; Clara Isabel Valero López,2025,Journal of Grid Computing,,,,,2,0.000,0.187,10.1007/s10723-025-09810-9,https://openalex.org/W4413129303,https://link.springer.com/content/pdf/10.1007/s10723-025-09810-9.pdf,openalex,,"Abstract The evolution from the Edge-Cloud Continuum to the Cognitive Computing Continuum (CCC) has introduced new challenges which necessitate advanced frameworks that integrate cognitive capabilities to enhance interoperability, adaptability, and resource efficiency. Considering insights from ongo" | |
| 34,,"Kalb-Ramond field, black holes and black strings in (2 + 1)D",Meseret Asrat,2025,Journal of High Energy Physics,,,,,2,0.000,0.181,10.1007/jhep08(2025)135,https://openalex.org/W4413471887,https://link.springer.com/content/pdf/10.1007/JHEP08(2025)135.pdf,openalex,,"A bstract New rotating dilaton black hole and black string solutions in three spacetime dimensions are obtained. The solutions are asymptotically flat and, they are exact in classical string theory. The black hole solutions have only a single horizon. Enclosed inside their horizons, they contain a c" | |
| 35,,Codepoietic Generation of Meaningful Information in the Evolving Biosphere,Abir U. Igamberdiev,2025,Entropy,,,,,2,0.000,0.181,10.3390/e27070672,https://openalex.org/W4411607412,https://www.mdpi.com/1099-4300/27/7/672/pdf?version=1750738707,openalex,,"Meaningful information represents reality in its potential form, and its actualization increases the system’s negentropy. Biological evolution leads to the expansion of meaningful information by generating new coding systems (codepoiesis). Through this expansion, any evolutionary change obtains func" | |
| 36,,Coriolis Factorizations and their Connections to Riemannian Geometry,Patrick M. Wensing; Johannes Englsberger; Jean-Jacques E. Slotine,2023,arXiv.org,,,,,2,0.000,0.158,10.48550/arXiv.2312.14425,https://www.semanticscholar.org/paper/4aeccd0f9f21f06a686422b3ef0c52455ca48a20,,semantic_scholar,,"Many energy-based control strategies for mechanical systems require the choice of a Coriolis factorization satisfying a skew-symmetry property. This paper (a) explores if and when a control designer has flexibility in this choice, (b) develops a canonical choice related to the Christoffel symbols, a" | |
| 37,,Hyper-graph regularized subspace clustering with skip connections for band selection of hyperspectral image,Meng Zeng; Bin Ning; Qiong Gu; Chunyang Hu; Shuijia Li,2022,Computer Science and Information Systems,,,,,2,0.000,0.154,10.2298/csis210830005z,https://www.semanticscholar.org/paper/280a90ebc45e900fd837290bd7f868c37dc04f9c,http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142200005Z,semantic_scholar,,"The Hughes phenomenon of Hyperspectral images (HSIs) with the hundreds of | |
| continuous narrow bands makes the computational cost of HSIs process ing | |
| high. Band selection is an effective way to solve such a problem and a lot | |
| of band selection methods have been proposed in recent years. In this paper" | |
| 38,,Regularity of CR maps into uniformly pseudo convex hyper surfaces and applications to proper holomorphic maps,Josef Greilhuber; B. Lamel,2022,ANNALI SCUOLA NORMALE SUPERIORE - CLASSE DI SCIENZE,,,,,2,0.000,0.135,10.2422/2036-2145.202105_009,https://www.semanticscholar.org/paper/076fb2e5f9317a8551e59d2beb7a1c0939f083e4,https://arxiv.org/pdf/2302.14016,semantic_scholar,,We study regularity properties of CR maps in positive codimension valued in pseudoconvex manifolds which carry a nontrivial Levi foliation. We introduce an invariant which can be used to deduce that any sufficiently regular CR map from a minimal manifold into such a foliated target is either generic | |
| 39,,Cross-Dimensional Mathematics: A Foundation For STP/STA,Daizhan Cheng,2024,,,,,,1,0.000,0.260,10.1007/s11425-024-2528-4,https://www.semanticscholar.org/paper/39270d175ed49f35e036ca21ee61e7490c5d627f,,semantic_scholar,,"A new mathematical structure, called the cross-dimensional mathematics (CDM), is proposed. The CDM considered in this paper consists of three parts: hyper algebra, hyper geometry, and hyper Lie group/Lie algebra. Hyper algebra proposes some new algebraic structures such as hyper group, hyper ring, a" | |
| 40,,Manifold Trajectories in Next-Token Prediction: From Replicator Dynamics to Softmax Equilibrium,Christopher R. Lee-Jenkins,2025,arXiv.org,,,,,1,0.000,0.190,10.48550/arXiv.2508.21186,https://www.semanticscholar.org/paper/5b675c8e73259f41c0ed2b9ab4dad68f21111dc2,,semantic_scholar,,"Decoding in large language models is often described as scoring tokens and normalizing with softmax. We give a minimal, self-contained account of this step as a constrained variational principle on the probability simplex. The discrete, normalization-respecting ascent is the classical multiplicative" | |
| 41,,Stepsize anything: A unified learning rate schedule for budgeted-iteration training,Anda Tang; Yiming Dong; Yutao Zeng; zhou Xun; Zhouchen Lin,2025,arXiv.org,,,,,1,0.000,0.188,10.48550/arXiv.2505.24452,https://www.semanticscholar.org/paper/5252fc9c44d42587da74fc166e18038fe8ee0263,,semantic_scholar,,"The expanding computational costs and limited resources underscore the critical need for budgeted-iteration training, which aims to achieve optimal learning within predetermined iteration budgets. While learning rate schedules fundamentally govern the performance of different networks and tasks, par" | |
| 42,,Federated Learning for Large-Scale Cloud Robotic Manipulation: Opportunities and Challenges,Obaidullah Zaland; Chanh Nguyen; Florian T. Pokorny; Monowar H. Bhuyan,2025,International Conference on Machine Learning and Computing,,,,,1,0.000,0.185,10.1109/ICMLC66258.2025.11280176,https://www.semanticscholar.org/paper/810506e46071c6581f9c2f608e584339fc713926,,semantic_scholar,,"Federated Learning (FL) is an emerging distributed machine learning paradigm, where the collaborative training of a model involves dynamic participation of devices to achieve broad objectives. In contrast, classical machine learning (ML) typically requires data to be located on-premises for training" | |
| 43,,A Connection Between Score Matching and Local Intrinsic Dimension,Eric Yeats; Aaron Jacobson; Darryl Hannan; Yiran Jia; Timothy Doster,2025,arXiv.org,,,,,1,0.000,0.184,10.48550/arXiv.2510.12975,https://www.semanticscholar.org/paper/6bcd7f677e1dbfc1463f4c1762e3a278fd2d692f,,semantic_scholar,,"The local intrinsic dimension (LID) of data is a fundamental quantity in signal processing and learning theory, but quantifying the LID of high-dimensional, complex data has been a historically challenging task. Recent works have discovered that diffusion models capture the LID of data through the s" | |
| 44,,Generalization of anomaly formula for time-reversal symmetry in (2+1)D abelian bosonic TQFTs,Ippo Orii,2025,Progress of Theoretical and Experimental Physics,,,,,1,0.000,0.182,10.1093/ptep/ptaf155,https://www.semanticscholar.org/paper/2ca3cbe3c539f227aec948406c9a403180511d7d,,semantic_scholar,," | |
| We study time-reversal symmetry in (2 + 1)D abelian bosonic topological phases. Time-reversal anomalies in such systems are classified by $\mathbb {Z}_2 \times \mathbb {Z}_2$ symmetry-protected topological (SPT) phases in (3 + 1)D, and can be diagnosed via partition functions on manifolds such as " | |
| 45,,Research on Time Series Prediction Model of Quantum Long Short Term Memory Network Fusion,Bing Han; Jian Kang; Hongyu Su,2025,Preprints.org,,,,,1,0.000,0.180,10.20944/preprints202508.0647.v1,https://openalex.org/W4413114546,https://www.preprints.org/frontend/manuscript/cd23a06aae90a6a104783f136fdc0cc1/download_pub,openalex,,This study proposes a novel hybrid prediction model (QGCN-LSTM) that combines quantum graph convolutional networks with classical LSTM. The model takes classical time series data as input and achieves classical quantum information conversion through a quantum encoding layer. Multi scale features are | |
| 46,,Neural Architecture Search for Hyperspectral Image Classification: A Comprehensive Review and Future Perspectives,Aili Wang; Xinyu Liu; Kang Zhang; Haoran Lv; Haibin Wu,2025,Remote Sensing,,,,,1,0.000,0.180,10.3390/rs17152727,https://openalex.org/W4413037406,https://www.mdpi.com/2072-4292/17/15/2727/pdf?version=1754553071,openalex,,"Hyperspectral image classification (HSIC) is a key task in the field of remote sensing, but the complex nature of hyperspectral data poses a serious challenge to traditional methods. Although deep learning significantly improves classification performance through automatic feature extraction, manual" | |
| 47,,Microstates of AdS5 black holes with hypermultiplets,Marina David; Annelien Vekemans,2025,Journal of High Energy Physics,,,,,1,0.000,0.180,10.1007/jhep07(2025)148,https://openalex.org/W4412403714,https://link.springer.com/content/pdf/10.1007/JHEP07(2025)148.pdf,openalex,,"A bstract We construct supersymmetric rotating AdS 5 black holes in 5d $$ \mathcal{N} $$ <mml:math xmlns:mml=""http://www.w3.org/1998/Math/MathML""> <mml:mi>N</mml:mi> </mml:math> = 2 gauged supergravity coupled to two vector multiplets and a universal hypermultiplet, and verify their microscopic coun" | |
| 48,,"A Unified 4D Quantum Projection Framework of Space, Time, and Measurement",Mazen Zaino,2025,,,,,,1,0.000,0.180,10.14293/pr2199.001746.v1,https://openalex.org/W4411509857,https://www.scienceopen.com/document_file/6cb529af-1a5b-4d7d-9a3e-114650db0c6c/ScienceOpenPreprint/A%20Unified%204D%20Quantum%20Projection%20Framework.pdf,openalex,,"This paper presents a novel theoretical framework that aims to unify the core principles of quantum mechanics, general relativity, and thermodynamics by introducing an extended spatial geometry incorporating a compactified fourth spatial dimension. The theory proposes that many of the counterintuiti" | |
| 49,,"A Survey of Task-Oriented Knowledge Graph Reasoning: Status, Applications, and Prospects",Guanglin Niu; Bo Li; Yangguang Lin,2025,,,,,,1,0.000,0.180,10.36227/techrxiv.174961563.32605293/v1,https://openalex.org/W4411222678,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.174961563.32605293/v1,openalex,, | |
| 50,,CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge,Yuxi Han; Jihe Wang; Danghui Wang,2024,arXiv.org,,,,,1,0.000,0.175,10.48550/arXiv.2405.19033,https://www.semanticscholar.org/paper/f5d6c679fcc0d9149abe51b9bea8905072593290,,semantic_scholar,,"Graph Neural Networks (GNNs) are computationally demanding and inefficient when applied to graph classification tasks in resource-constrained edge scenarios due to their inherent process, involving multiple rounds of forward and backward propagation. As a lightweight alternative, Hyper-Dimensional C" | |
| 51,,On the selection of a proper connection in describing the dynamics of constrained mechanical systems,S. Natsiavas; P. Passas; K. Tzaferis,2023,Nonlinear dynamics,,,,,1,0.000,0.164,10.1007/s11071-023-08326-9,https://www.semanticscholar.org/paper/a95c3704bec9d3c60ba0bf06ed6c9cc2d8d10392,https://link.springer.com/content/pdf/10.1007/s11071-023-08326-9.pdf,semantic_scholar,,"This study is focused on a critical issue related to the direct and consistent application of Newton’s law of motion to a special but large class of mechanical systems, involving equality motion constraints. For these systems, it is advantageous to employ the general analytical dynamics framework, w" | |
| 52,,An efficient constraint method for solving planning problems under end-effector constraints,Yahao Wang; Zhen Li; Yanghong Li; Erbao Dong,2024,Industrial robot,,,,,1,0.000,0.164,10.1108/ir-10-2023-0251,https://www.semanticscholar.org/paper/332f84439359c8b9b288e2a00ffbcc6721a94a8b,,semantic_scholar,," | |
| Purpose | |
| In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner. | |
| Design/methodology/approach | |
| In this work" | |
| 53,,Manifold Learning for fMRI time-varying FC,J. Gonzalez-Castillo; Isabel S. Fernandez; K. Lam; D. Handwerker; Francisco Pereira,2023,bioRxiv,,,,,1,0.000,0.157,10.1101/2023.01.14.523992,https://www.semanticscholar.org/paper/ef84c2d8052b5af43ae95579f7943c5594cf41ed,https://www.biorxiv.org/content/biorxiv/early/2023/01/16/2023.01.14.523992.full.pdf,semantic_scholar,, | |
| 54,,Thermodynamic geometry of spin-one lattice models. I. Spin and quadrupolar orders and critical scaling functions in one dimension.,Riekshika Sanwari; A. Sahay,2022,Physical Review E,,,,,1,0.000,0.126,10.1103/physreve.105.034134,https://www.semanticscholar.org/paper/c505b50afe4592017ef39e99e68043946187f8ae,,semantic_scholar,,"State space Riemannian geometry is obtained for the one-dimensional Blume-Emery-Griffiths model and its Blume-Capel and Griffiths model limits, and its (pseudo)critical as well as noncritical parameter regimes are extensively investigated. Two codimension one geometries are obtained by taking suitab" | |
| 55,,Integral formulas for a foliated sub-Riemannian manifold,V. Rovenski,2021,European Journal of Mathematics,,,,,1,0.000,0.116,10.1007/s40879-023-00593-5,https://www.semanticscholar.org/paper/cb380c2885dfb70009c60e498cd130d99c1b8595,,semantic_scholar,,"We apply the notion of foliation to a nonholonomic manifold, which was introduced for the geometric interpretation of constrained systems in mechanics. We prove a series of integral formulas for a foliated sub-Riemannian manifold, that is, a Riemannian manifold equipped with a distribution $${{\math" | |
| 56,,Hyper-Laplacian Regularized Low-Rank Collaborative Representation Classification,Shun Xu; Wenwen Shen,2020,International Conference on Advanced Computational Intelligence,,,,,1,0.000,0.109,10.1109/ICACI49185.2020.9177524,https://www.semanticscholar.org/paper/d00180bafb3fffc3ee95496a0d875909379aaf3f,,semantic_scholar,,"Face recognition is an important branch of computer vision. Domestic and foreign scholars have proposed many algorithms to improve the face recognition rate. However, when the training sample and the test sample are exposed to light, occlusion or contamination, the performance of the proposed algori" | |
| 57,,A pr 2 02 1 BFV extensions and their obstructions in mechanical systems with Lie-2 symmetry,Aliaksandr Hancharuk; T. Strobl,2021,,,,,,1,0.000,0.100,,https://www.semanticscholar.org/paper/c082909b9f5bae31da49ff578574567483d629b2,,semantic_scholar,, | |
| 58,,Hyperspectral subpixel unmixing via an integrative framework,Chunzhi Li; Xiaohua Chen; Yuan Zhang,2020,,,,,,1,0.000,0.099,10.1080/01431161.2020.1783711,https://www.semanticscholar.org/paper/c947cdc476ae597671bb4d4f923118b60eadfefb,,semantic_scholar,,"ABSTRACT In hyperspectral applications, spectral unmixing (SU) is an important technology to obtain the endmembers and the fractional land covers. Spectral variability, outliers, and nonlinearity are three challenging issues, causing SU to extract endmembers and corresponding abundance maps inaccura" | |
| 59,9FqARW7dwB,Hyper-Connections,Defa Zhu; Hongzhi Huang; Zihao Huang; Yutao Zeng; Yunyao Mao,2025,ICLR 2025,main,Poster,"foundation or frontier models, including LLMs",Network Architecture;Residual Connections;LLMs;Pre-training,0,1.000,0.616,,https://iclr.cc/virtual/2025/poster/30709,https://openreview.net/pdf?id=9FqARW7dwB,offline_iclr,,"We present hyper-connections, a simple yet effective method that can serve as an alternative to residual connections. This approach specifically addresses common drawbacks observed in residual connection variants, such as the seesaw effect between gradient vanishing and representation collapse. Theo" | |
| 60,A5AejTTloS,Value-Alignment via Safe Semantic Manifold-Constrained Latent Diffusion,,2026,ICLR 2026,main,Active,"alignment, fairness, safety, privacy, and societal considerations",value alignment; diffusion model; Manifold-Constrained,0,0.731,0.432,,https://openreview.net/forum?id=A5AejTTloS,,offline_iclr,,"LLM-based detoxification often shifts explicit toxicity into subtler forms: profanities vanish while harm persists through insinuations, stereotypes, microaggressions, and subtly discriminatory framing. We reformulate detoxification from a value-alignment perspective as a multi-principle constrained" | |
| 61,ECc2td0LCZ,Manifold-Constrained Gaussian Process Inference for One-shot Learning of Unknown Ordinary Differential Equations,,2026,ICLR 2026,main,Active,"applications to physical sciences (physics, chemistry, biology, etc.)",Gaussian Process;ODE learning,0,0.642,0.401,,https://openreview.net/forum?id=ECc2td0LCZ,,offline_iclr,,"Learning unknown ordinary differential equations (ODEs) from a single trajectory of scarce, noisy data is challenging, especially with partial observability. We introduce MAGI-X, an integration-free framework that couples a neural vector field with a Gaussian process prior over trajectories and enfo" | |
| 62,VMV8gefvq8,MCNC: Manifold-Constrained Reparameterization for Neural Compression,Chayne Thrash; Reed Andreas; Ali Abbasi; Parsa Nooralinejad; Soroush Abbasi Koohpayegani,2025,ICLR 2025,main,Poster,"other topics in machine learning (i.e., none of the above)",Model Compression;LoRA;PEFT;Transformers;ViT,0,0.683,0.399,,https://iclr.cc/virtual/2025/poster/29420,https://openreview.net/pdf?id=VMV8gefvq8,offline_iclr,,"The outstanding performance of large foundational models across diverse tasks, | |
| from computer vision to speech and natural language processing, has significantly | |
| increased their demand. However, storing and transmitting these models poses | |
| significant challenges due to their massive size (e.g., 750GB " | |
| 63,32385,Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI,Won Jun Kim; Hyungjin Chung; Jaemin Kim; Sangmin Lee; Byeongsu Sim,2025,CVPR 2025,main,Poster,,,0,0.666,0.394,,https://cvpr.thecvf.com/virtual/2025/poster/32385,https://openaccess.thecvf.com/content/CVPR2025/papers/Kim_Derivative-Free_Diffusion_Manifold-Constrained_Gradient_for_Unified_XAI_CVPR_2025_paper.pdf,offline_cvpr,,"Gradient-based methods are a prototypical family of ""explainability for AI"" (XAI) techniques, especially for image-based models. However, they (1) require white-box access to models, (2) are vulnerable to adversarial attacks, and (3) produce attributions that lie off the image manifold, leading to e" | |
| 64,xxY8d4rnSb,ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation,Cédric Rommel; Victor Letzelter; Nermin Samet; Renaud Marlet; Matthieu Cord,2024,NIPS 2024,main,Poster,machine_vision,human pose estimation;depth ambiguity;multiple choice learning,0,0.727,0.389,,https://neurips.cc/virtual/2024/poster/93050,https://openreview.net/pdf?id=xxY8d4rnSb,offline_nips,,"We propose ManiPose, a manifold-constrained multi-hypothesis model for human-pose 2D-to-3D lifting. We provide theoretical and empirical evidence that, due to the depth ambiguity inherent to monocular 3D human pose estimation, traditional regression models suffer from pose-topology consistency issue" | |
| 65,UTNZKl5BUc,Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization,seyed amir hossein saberi; Amir Najafi; Amin Behjati; Ala Emrani; Yasaman Zolfimoselo,2024,NIPS 2024,main,Poster,learning_theory,Gradual Domain Adaptation;Distributionally Robust Optimization;Generalization Bound;Error Propagation Characterization,0,0.677,0.379,,https://neurips.cc/virtual/2024/poster/94967,https://openreview.net/pdf?id=UTNZKl5BUc,offline_nips,,"The aim of this paper is to address the challenge of gradual domain adaptation within a class of manifold-constrained data distributions. In particular, we consider a sequence of $T\ge2$ data distributions $P_1,\ldots,P_T$ undergoing a gradual shift, where each pair of consecutive measures $P_i,P_{i" | |
| 66,E77uvbOTtp,CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models,Hyungjin Chung; Jeongsol Kim; Geon Yeong Park; Hyelin Nam; Jong Chul Ye,2025,ICLR 2025,main,Poster,generative models,Diffusion models;Manifold;Classifier-free guidance,0,0.603,0.367,,https://iclr.cc/virtual/2025/poster/30421,https://openreview.net/pdf?id=E77uvbOTtp,offline_iclr,,"Classifier-free guidance (CFG) is a fundamental tool in modern diffusion models for text-guided generation. Although effective, CFG has notable drawbacks. For instance, DDIM with CFG lacks invertibility, complicating image editing; furthermore, high guidance scales, essential for high-quality output" | |
| 67,61jN0L0aoJ,Beyond Minimax: Structure-Aware Learning for Differential Games,,2026,ICLR 2026,main,Active,"neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.)",pursuit-evasion game;calculus of variations;pontryagin's maximum principle,0,0.377,0.319,,https://openreview.net/forum?id=61jN0L0aoJ,,offline_iclr,,"A central challenge in artificial intelligence is to design agents that solve structured engineering problems, such as zero-sum differential games, without handcrafted solutions or expert demonstrations. Differential games capture multi-agent interactions with opposing objectives, where optimal stra" | |
| 68,ghhKZ0NaQN,DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration,Hebaixu Wang; Jing Zhang; Haonan Guo; Di Wang; Jiayi Ma,2025,NIPS 2025,main,Poster,deep_learning,Image restoration;diffusion generalist solver;universal posterior sampling;deep learning,0,0.380,0.299,,https://openreview.net/forum?id=ghhKZ0NaQN,,offline_nips,,"Diffusion models have achieved remarkable progress in universal image restoration. However, existing methods perform naive inference in the reverse process, which leads to cumulative errors under limited sampling steps and large step intervals. Moreover, they struggle to balance the commonality of d" | |
| 69,RAC3ng3TSN,Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees,Steffen Schotthöfer; M. Paul Laiu,2025,ICLR 2025,main,Reject,optimization,Federated Learning;Low-Rank;Model Compression;Efficient Federated Learning,0,0.378,0.298,,https://openreview.net/forum?id=RAC3ng3TSN,,offline_iclr,,We propose a federated dynamical low-rank training (FeDLRT) scheme to reduce client compute and communication costs - two significant performance bottlenecks in horizontal federated learning. Our method builds upon dynamical low-rank splitting schemes for manifold-constrained optimization to create | |
| 70,QQqDBRRslp,Toward a Unified Geometry Understanding : Riemannian Diffusion Framework for Graph Generation and Prediction,Yisen Gao; Xingcheng Fu; Qingyun Sun; Jianxin Li; Xianxian LI,2025,NIPS 2025,main,Poster,deep_learning,Graph Generation;Hyperbolic Graph Learning;Riemannian Manifold;Graph Learning,0,0.335,0.296,,https://openreview.net/forum?id=QQqDBRRslp,,offline_nips,,"Graph diffusion models have made significant progress in learning structured graph data and have demonstrated strong potential for predictive tasks. Existing approaches typically embed node, edge, and graph-level features into a unified latent space, modeling prediction tasks including classificatio" | |
| 71,DsEhqQtfAG,Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems,Hyungjin Chung; Suhyeon Lee; Jong Chul Ye,2024,ICLR 2024,main,Poster,generative models,Diffusion models; Inverse problems; Krylov subspace,0,0.333,0.265,,https://iclr.cc/virtual/2024/poster/19121,https://openreview.net/pdf?id=DsEhqQtfAG,offline_iclr,,"Krylov subspace, which is generated by multiplying a given vector by the matrix of a linear transformation and its successive powers, has been extensively studied in classical optimization literature to design algorithms that converge quickly for large linear inverse problems. For example, the conj" | |
| 72,CxUuCydMDU,Diffusion Probabilistic Models for Structured Node Classification,Hyosoon Jang; Seonghyun Park; Sangwoo Mo; Sungsoo Ahn,2023,NIPS 2023,main,Poster,,diffusion model;graph neural network;structured prediction;node classification,0,0.364,0.254,,https://nips.cc/virtual/2023/poster/72405,https://openreview.net/pdf?id=CxUuCydMDU,offline_nips,,"This paper studies structured node classification on graphs, where the predictions should consider dependencies between the node labels. In particular, we focus on solving the problem for partially labeled graphs where it is essential to incorporate the information in the known label for predicting " | |
| 73,,mHC: Manifold-Constrained Hyper-Connections,Zhenda Xie; Yixuan Wei; Huanqi Cao; Chenggang Zhao; Chengqi Deng,2025,arXiv,,,,,0,0.000,0.249,,http://arxiv.org/abs/2512.24880v1,https://arxiv.org/pdf/2512.24880v1,arxiv,,"Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream width and diversifying connectivity patterns. While yielding substantial performance gains, this diversification fundame" | |
| 74,,Hyper-Generalized Weakly Symmetric Para-Sasakian Manifolds and Their Geometric Properties,B. Thangjam; M. Devi,2025,BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS,,,,,0,0.000,0.225,10.31489/2025m2/241-251,https://www.semanticscholar.org/paper/c673f9021fdb127edcebdf60239985331b4b693c,,semantic_scholar,,"This paper examines para-Sasakian manifolds that satisfy a hyper-generalized weakly symmetric curvature condition. The conditions under which such a manifold with a hyper-generalized weakly symmetric curvature condition satisfies the η-Einstein manifold are established. Furthermore, the geometric be" | |
| 75,,Generative Bayesian Hyperparameter Tuning,Hedibert Lopes; Nick Polson; Vadim Sokolov,2025,arXiv,,,,,0,0.000,0.223,,http://arxiv.org/abs/2512.20051v1,https://arxiv.org/pdf/2512.20051v1,arxiv,,"\noindent Hyper-parameter selection is a central practical problem in modern machine learning, governing regularization strength, model capacity, and robustness choices. Cross-validation is often computationally prohibitive at scale, while fully Bayesian hyper-parameter learning can be difficult due" | |
| 76,13817,Escaping from saddle points on Riemannian manifolds,Yue Sun; Nicolas Flammarion; Maryam Fazel,2019,NIPS 2019,main,Poster,,,0,0.458,0.218,,https://nips.cc/virtual/2019/poster/13817,https://papers.nips.cc/paper_files/paper/2019/file/24e01830d213d75deb99c22b9cd91ddd-Paper.pdf,offline_nips,,"We consider minimizing a nonconvex, smooth function $f$ on a Riemannian manifold $\mathcal{M}$. We show that a perturbed version of the gradient descent algorithm converges to a second-order stationary point for this problem (and hence is able to escape saddle points on the manifold). While the unco" | |
| 77,,Randers metrics with compatible linear connections: a coordinate-free approach,M'ark Ol'ah; Csaba Vincze,2025,Journal of Geometry,,,,,0,0.000,0.218,10.1007/s00022-025-00755-8,https://www.semanticscholar.org/paper/ec2c66f5976abfcd2f630903c6e1a735eefa2a97,,semantic_scholar,,A Randers space is a differentiable manifold equipped with a Randers metric. It is the sum of a Riemannian metric and a one-form on the base manifold. The compatibility of a linear connection with the metric means that the parallel transports preserve the Randers norm of tangent vectors. The existen | |
| 78,,"Arithmetic monodromy of hyper-K\""ahler varieties over $p$-adic fields",Kazuhiro Ito; Tetsushi Ito; Teruhisa Koshikawa; Teppei Takamatsu; Haitao Zou,2025,,,,,,0,0.000,0.213,,https://www.semanticscholar.org/paper/73641545c3fda2c186b4b41aa3e27f19d7d96bc6,,semantic_scholar,,"In this paper, we study the $p$-adic and $\ell$-adic monodromy operators associated with hyper-K\""ahler varieties over $p$-adic fields, in connection with Looijenga-Lunts-Verbitsky Lie algebras. We investigate a conjectural relation between the nilpotency indices of these monodromy operators on high" | |
| 79,,Manifold-constrained Hamilton-Jacobi Reachability Learning for Decentralized Multi-Agent Motion Planning,Qingyi Chen; Ruiqi Ni; Jun Kim; Ahmed H. Qureshi,2025,arXiv,,,,,0,0.000,0.205,,http://arxiv.org/abs/2511.03591v1,https://arxiv.org/pdf/2511.03591v1,arxiv,,"Safe multi-agent motion planning (MAMP) under task-induced constraints is a critical challenge in robotics. Many real-world scenarios require robots to navigate dynamic environments while adhering to manifold constraints imposed by tasks. For example, service robots must carry cups upright while avo" | |
| 80,,Efficient Manifold-Constrained Neural ODE for High-Dimensional Datasets,Muhao Guo; Haoran Li; Yang Weng,2025,arXiv,,,,,0,0.000,0.204,,http://arxiv.org/abs/2510.04138v1,https://arxiv.org/pdf/2510.04138v1,arxiv,,"Neural ordinary differential equations (NODE) have garnered significant attention for their design of continuous-depth neural networks and the ability to learn data/feature dynamics. However, for high-dimensional systems, estimating dynamics requires extensive calculations and suffers from high trun" | |
| 81,,A Single-Loop First-Order Algorithm for Linearly Constrained Bilevel Optimization,Wei Shen; Jiawei Zhang; Minhui Huang; Cong Shen,2025,arXiv.org,,,,,0,0.000,0.202,10.48550/arXiv.2510.24710,https://www.semanticscholar.org/paper/9db6d6af5761c0e98bac91d2cf09af65880ca0e9,,semantic_scholar,,"We study bilevel optimization problems where the lower-level problems are strongly convex and have coupled linear constraints. To overcome the potential non-smoothness of the hyper-objective and the computational challenges associated with the Hessian matrix, we utilize penalty and augmented Lagrang" | |
| 82,,Lagrangian Dual Sections: A Topological Perspective on Hidden Convexity,Venkat Chandrasekaran; Timothy Duff; Jose Israel Rodriguez; Kevin Shu,2025,,,,,,0,0.000,0.199,,https://www.semanticscholar.org/paper/702a8cf538d6f51d0b98a89a34a5d1d55b40b3ac,,semantic_scholar,,"Hidden convexity is a powerful idea in optimization: under the right transformations, nonconvex problems that are seemingly intractable can be solved efficiently using convex optimization. We introduce the notion of a Lagrangian dual section of a nonlinear program defined over a topological space, a" | |
| 83,,"Hyperk\""ahler structures on leaves of hyper-Lie Poisson manifolds",Dadi Ni; Kaichuan Qi,2025,,,,,,0,0.000,0.199,,https://www.semanticscholar.org/paper/786f152b5c97bc7c34f3dd3bad4a694af13c23d8,,semantic_scholar,,"Due to its rich structure and close connection with gauge theory, hyperk\""ahler manifolds have attracted increasing interest. Using infinite dimensional hyperk\""ahler reduction, Kronheimer proved that certain adjoint orbits of complexified semisimple Lie algebras admits hyperk\""ahler structures. Lat" | |
| 84,,On the rigidity of special and exceptional geometries with torsion a closed $3$-form,Georgios Papadopoulos,2025,arXiv,,,,,0,0.000,0.199,,http://arxiv.org/abs/2511.20568v2,https://arxiv.org/pdf/2511.20568v2,arxiv,,"We demonstrate that all Riemannian manifolds $(M, g, H)$ that admit a connection $\hat\nabla$ with torsion a 3-form $H$, which is both closed $d H=0$ and $\hat\nabla$-covariantly constant, are locally isometric to a product $N\times G$, where $G$ is a semisimple group and $N$ is a Riemannian manifol" | |
| 85,,Toward Hyper-Dimensional Connectivity in Beyond 6G: A Conceptual Framework,Ekram Hossain; Angelo Vera-Rivera,2025,arXiv,,,,,0,0.000,0.199,,http://arxiv.org/abs/2510.12896v1,https://arxiv.org/pdf/2510.12896v1,arxiv,,"Cellular wireless networks enable mobile broadband connectivity for Internet-based applications through their radio access and core network infrastructure. While Fifth-Generation (5G) cellular systems are currently being deployed, ongoing research on cellular technologies primarily focuses on Sixth-" | |
| 86,,Stable Robot Motions on Manifolds: Learning Lyapunov-Constrained Neural Manifold ODEs,David Boetius; Abdelrahman Abdelnaby; Ashok Kumar; Stefan Leue; Abdalla Swikir,2025,arXiv,,,,,0,0.000,0.197,,http://arxiv.org/abs/2510.05707v1,https://arxiv.org/pdf/2510.05707v1,arxiv,,"Learning stable dynamical systems from data is crucial for safe and reliable robot motion planning and control. However, extending stability guarantees to trajectories defined on Riemannian manifolds poses significant challenges due to the manifold's geometric constraints. To address this, we propos" | |
| 87,,"Lie algebroids, quantum Poisson algebroids, and Lie algebroid connections",Satyendra Kumar Mishra; A. Sarkar,2025,,,,,,0,0.000,0.196,,https://www.semanticscholar.org/paper/4105091889345f991b2875d21437a69e73fd6b4e,,semantic_scholar,,"In this paper, we consider Lie algebroids over commutative ringed spaces. Lie algebroids over ringed spaces unify the existing notion of Lie algebroids over smooth manifolds, complex manifolds, analytic spaces, algebraic varieties, and schemes. We show that the universal enveloping algebroid of a Li" | |
| 88,,Fundamental Limitations of QAOA on Constrained Problems and a Route to Exponential Enhancement,Chinonso Onah; Kristel Michielsen,2025,arXiv,,,,,0,0.000,0.196,,http://arxiv.org/abs/2511.17259v1,https://arxiv.org/pdf/2511.17259v1,arxiv,,"We study fundamental limitations of the generic Quantum Approximate Optimization Algorithm (QAOA) on constrained problems where valid solutions form a low dimensional manifold inside the Boolean hypercube, and we present a provable route to exponential improvements via constraint embedding. Focusing" | |
| 89,,Cech - de Rham Chern character on the stack of holomorphic vector bundles,Cheyne Glass; T. Tradler; M. Zeinalian,2025,,,,,,0,0.000,0.195,,https://www.semanticscholar.org/paper/1231982e3a59d14420806f9e0aa5b6d34d2537d5,,semantic_scholar,,We provide a formula for the Chern character of a holomorphic vector bundle in the hyper-cohomology of the de Rham complex of holomorphic sheaves on a complex manifold. This Chern character can be thought of as a completion of the Chern character in Hodge cohomology obtained as the trace of the expo | |
| 90,,Harmonising Reality and Professional Practice: Pedagogies of Inclusive Teaching and Connected Learning,R. Dlamini,2025,Working papers,,,,,0,0.000,0.195,10.56059/pcf11.1266,https://www.semanticscholar.org/paper/eddb430093c146903f42038d1797df458dc67b45,,semantic_scholar,,"Globally, there is a growing interest in achieving greater educational inclusion to address the persistent inequalities related to education disparities and social mobility. However, the focus of this study is the persistent high levels of inequality, poverty and unemployment in South Africa that re" | |
| 91,,Trajectory Optimization by Successive Pseudospectral Convexification on Riemannian Manifolds,Tatsuya Narumi; Shin-ichiro Sakai,2025,arXiv,,,,,0,0.000,0.195,,http://arxiv.org/abs/2512.09551v1,https://arxiv.org/pdf/2512.09551v1,arxiv,,"This paper proposes an intrinsic pseudospectral convexification framework for optimal control problems with manifold constraints. While successive pseudospectral convexification combines spectral collocation with successive convexification, classical pseudospectral methods are not geometry-consisten" | |
| 92,,The algebraic square of an irreducible complex spinor,Alejandro Gil-Garc'ia; C. Shahbazi,2025,,,,,,0,0.000,0.194,,https://www.semanticscholar.org/paper/7a97a602f138d4259eac9619fc1948877dca3b10,,semantic_scholar,,"We characterize, in every dimension and signature, the algebraic squares of an irreducible complex spinor as a pair of exterior forms satisfying a prescribed system of algebraic relations that we present in terms of the geometric product of the underlying quadratic vector space. As a result, we obta" | |
| 93,,"Secrets of the Goo: The genome assembly of the Pacific banana slug, Ariolimax columbianus",Max Genetti; Merly Escalona; Cade Mirchandani; Jonas Oppenheimer; E. Beraut,2025,Journal of Heredity,,,,,0,0.000,0.193,10.1093/jhered/esaf002,https://www.semanticscholar.org/paper/29dea4859e36ffe56831ffd1850a48666ae0b38e,,semantic_scholar,,"Abstract The Pacific banana slug, Ariolimax columbianus, is endemic to the forests of the Pacific Northern West. Found throughout the coastal foothills and mountains of California, the hermaphroditic molluscs Ariolimax spp. are niche-constrained, hyper-localized, and phenotypically diverse. The evol" | |
| 94,,Geometrically robust least squares through manifold optimization,Jeremy Coulson; Alberto Padoan; Cyrus Mostajeran,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2511.03644v1,https://arxiv.org/pdf/2511.03644v1,arxiv,,"This paper presents a methodology for solving a geometrically robust least squares problem, which arises in various applications where the model is subject to geometric constraints. The problem is formulated as a minimax optimization problem on a product manifold, where one variable is constrained t" | |
| 95,,Channel-Constrained Markovian Quantum Diffusion Model from Open System Perspective,Qin-Sheng Zhu; Geng Chen; Lian-Hui Yu; Xiaodong Xing; Xiao-Yu Li,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2511.12221v1,https://arxiv.org/pdf/2511.12221v1,arxiv,,"We present a channel-constrained Markovian quantum diffusion (CCMQD) model that prepares quantum states by rigorously framing the generative process within the dynamics of open quantum systems. Our model interprets the forward diffusion process as natural decoherence using quantum master equations, " | |
| 96,,Quotient Manifold Optimization for Spectral Compressed Sensing,Wenlong Wang; Wen Huang; Zai Yang,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2511.19108v1,https://arxiv.org/pdf/2511.19108v1,arxiv,,"Spectral compressed sensing involves reconstructing a spectral-sparse signal from a subset of uniformly spaced samples, with applications in radar imaging and wireless channel estimation. By fully exploiting the signal structures, this problem is formulated as a rank-constrained semidefinite program" | |
| 97,,Quantumness via Discrete Structures,Ravi Kunjwal,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2512.10063v2,https://arxiv.org/pdf/2512.10063v2,arxiv,,"Quantum theory departs from classical probabilistic theories in foundational ways. These departures--termed quantumness here--power quantum information and computation. This thesis charts the role of discrete structures in assessing quantumness, synthesizing elements of my postdoctoral research thro" | |
| 98,,"Signatures of real-space geometry, topology, and metric tensor in quantum transport in periodically corrugated spaces",Benjamin Schwager; Theresa Appel; Jamal Berakdar,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2512.16846v1,https://arxiv.org/pdf/2512.16846v1,arxiv,,The motion of a quantum particle constrained to a two-dimensional non-compact Riemannian manifold with non-trivial metric can be described by a flat-space Schroedinger-type equation at the cost of introducing local mass and metric and geometry-induced effective potential with no classical counterpar | |
| 99,,HySim-LLM: Embedding-Weighted Fine-Tuning Bounds and Manifold Denoising for Domain-Adapted LLMs,Majid Jaberi-Douraki; Hossein Sholehrasa; Xuan Xu; Remya Ampadi Ramachandran,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2510.07796v1,https://arxiv.org/pdf/2510.07796v1,arxiv,,"The extraction and standardization of pharmacokinetic (PK) information from scientific literature remain significant challenges in computational pharmacology, which limits the reliability of data-driven models in drug development. Large language models (LLMs) have achieved remarkable progress in tex" | |
| 100,,PDE-Free Mass-Constrained Learning of Complex Systems with Hidden States: The crowd dynamics case,Gianmaria Viola; Alessandro Della Pia; Lucia Russo; Ioannis Kevrekidis; Constantinos Siettos,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2510.17657v2,https://arxiv.org/pdf/2510.17657v2,arxiv,,"We propose a machine learning framework based on the next-generation Equation-Free algorithm for learning the spatio-temporal dynamics of mass-constrained complex systems with hidden states, whose dynamics can in principle be described by PDEs, but lack explicit models. In these cases, some variable" | |
| 101,,AL-Net: Adaptive Learning for Enhanced Cell Nucleus Segmentation in Pathological Images,Zhuping Chen; Sheng-Lung Peng; Rui Yang; Ming Zhao; Chaolin Zhang,2025,Electronics,,,,,0,0.000,0.193,10.3390/electronics14173507,https://www.semanticscholar.org/paper/85fa9539b6139e5c61a9364cb288675c0ae7e542,,semantic_scholar,,"Precise segmentation of cell nuclei in pathological images is the foundation of cancer diagnosis and quantitative analysis, but blurred boundaries, scale variability, and staining differences have long constrained its reliability. To address this, this paper proposes AL-Net—an adaptive learning netw" | |
| 102,,Physics-Constrained Neural Dynamics: A Unified Manifold Framework for Large-Scale Power Flow Computation,Xuezhi Liu,2025,arXiv,,,,,0,0.000,0.193,,http://arxiv.org/abs/2512.01207v1,https://arxiv.org/pdf/2512.01207v1,arxiv,,"Power flow analysis is a fundamental tool for power system analysis, planning, and operational control. Traditional Newton-Raphson methods suffer from limitations such as initial value sensitivity and low efficiency in batch computation, while existing deep learning-based power flow solvers mostly r" | |
| 103,,Semantic Geometry for policy-constrained interpretation,Nikit Phadke,2025,arXiv,,,,,0,0.000,0.192,,http://arxiv.org/abs/2512.14731v1,https://arxiv.org/pdf/2512.14731v1,arxiv,,"We present a geometric framework for policy-constrained semantic interpretation that provably prevents hallucinated commitments in high-stakes domains. Semantic meaning is represented as direction on a unit sphere, evidence is modeled as sets of witness vectors, and admissible interpretations corres" | |
| 104,,Necessary and sufficient conditions for high dimensional Central Limit Theorem under moment conditions,Debraj Das; Soumendra Lahiri,2025,arXiv,,,,,0,0.000,0.192,,http://arxiv.org/abs/2512.22312v1,https://arxiv.org/pdf/2512.22312v1,arxiv,,"High dimensional central limit theorems (the CLTs) have been extensively studied in recent years under a variety of sufficient moment conditions connecting the dimension growth rate with the tail decay rate. In this article, we investigate whether the existing moment conditions are also necessary un" | |
| 105,569fe8abe2,Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach,Riccardo Bonalli; Abhishek Cauligi; Andrew Bylard; Thomas Lew; Marco Pavone,2019,RSS 2019,main,Poster,,,0,0.385,0.192,,https://www.roboticsproceedings.org/rss15/p78.html,https://www.roboticsproceedings.org/rss15/p78.pdf,offline_rss,,"Sequential Convex Programming (SCP) has recently gained popularity as a tool for trajectory optimization due to its sound theoretical properties and practical performance. Yet, most SCP-based methods for trajectory optimization are restricted to Euclidean settings, which precludes their application " | |
| 106,,Gradient-descent methods for quantum detector tomography,Amanuel Anteneh; Olivier Pfister,2025,arXiv,,,,,0,0.000,0.192,,http://arxiv.org/abs/2511.14579v1,https://arxiv.org/pdf/2511.14579v1,arxiv,,We present a technique for performing quantum detector tomography (QDT) of phase insensitive quantum detectors using gradient descent-based optimization to learn the positive operator-valued measure (POVM) that best describes the data collected using the detector under study. We numerically benchmar | |
| 107,,Asymmetric rational reductions of 2D-Toda hierarchy and a generalized Frobenius manifold,Haonan Qu; Qiulan Zhao,2025,arXiv,,,,,0,0.000,0.192,,http://arxiv.org/abs/2510.04151v1,https://arxiv.org/pdf/2510.04151v1,arxiv,,"We study the local bihamiltonian structures of the asymmetric rational reductions of the 2D-Toda hierarchy (RR2T) of types $(2,1)$ and $(1,2)$ at the full-dispersive level, and construct a three-dimensional generalized Frobenius manifold with non-flat unity associated with the $(2,1)$-type. Furtherm" | |
| 108,,ManifoldFormer: Geometric Deep Learning for Neural Dynamics on Riemannian Manifolds,Yihang Fu; Lifang He; Qingyu Chen,2025,arXiv,,,,,0,0.000,0.192,,http://arxiv.org/abs/2511.16828v1,https://arxiv.org/pdf/2511.16828v1,arxiv,,"Existing EEG foundation models mainly treat neural signals as generic time series in Euclidean space, ignoring the intrinsic geometric structure of neural dynamics that constrains brain activity to low-dimensional manifolds. This fundamental mismatch between model assumptions and neural geometry lim" | |
| 109,,Robust Graph Condensation via Classification Complexity Mitigation,Jiayi Luo; Qingyun Sun; Beining Yang; Haonan Yuan; Xingcheng Fu,2025,arXiv,,,,,0,0.000,0.191,,http://arxiv.org/abs/2510.26451v2,https://arxiv.org/pdf/2510.26451v2,arxiv,,"Graph condensation (GC) has gained significant attention for its ability to synthesize smaller yet informative graphs. However, existing studies often overlook the robustness of GC in scenarios where the original graph is corrupted. In such cases, we observe that the performance of GC deteriorates s" | |
| 110,,Riemannian Bilevel Optimization with Gradient Aggregation,Zhuo Chen; Xinjian Xu; Shihui Ying; Tieyong Zeng,2025,arXiv,,,,,0,0.000,0.191,,http://arxiv.org/abs/2510.15305v1,https://arxiv.org/pdf/2510.15305v1,arxiv,,"Bilevel optimization (BLO) offers a principled framework for hierarchical decision-making and has been widely applied in machine learning tasks such as hyperparameter optimization and meta-learning. While existing BLO methods are mostly developed in Euclidean spaces, many real-world problems involve" | |
| 111,,Manifold Decoders: A Framework for Generative Modeling from Nonlinear Embeddings,Riddhish Thakare; Kingdom Mutala Akugri,2025,arXiv,,,,,0,0.000,0.191,,http://arxiv.org/abs/2510.13622v1,https://arxiv.org/pdf/2510.13622v1,arxiv,,"Classical nonlinear dimensionality reduction (NLDR) techniques like t-SNE, Isomap, and LLE excel at creating low-dimensional embeddings for data visualization but fundamentally lack the ability to map these embeddings back to the original high-dimensional space. This one-way transformation limits th" | |
| 112,,Local Path Optimization in The Latent Space Using Learned Distance Gradient,Jiawei Zhang; Chengchao Bai; Wei Pan; Tianhang Liu; Jifeng Guo,2025,arXiv,,,,,0,0.000,0.190,10.1109/IROS60139.2025.11247535,http://arxiv.org/abs/2512.24272v1,https://arxiv.org/pdf/2512.24272v1,arxiv,,"Constrained motion planning is a common but challenging problem in robotic manipulation. In recent years, data-driven constrained motion planning algorithms have shown impressive planning speed and success rate. Among them, the latent motion method based on manifold approximation is the most efficie" | |
| 113,,HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization,Zeyang Li; Kaveh Alim; Navid Azizan,2025,arXiv,,,,,0,0.000,0.190,,http://arxiv.org/abs/2511.08425v2,https://arxiv.org/pdf/2511.08425v2,arxiv,,"Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distributions and enabling flexible guidance at inference time. Many downstream applications, however, demand enforcing hard constraints on generated samples " | |
| 114,,The Geometry of Grokking: Norm Minimization on the Zero-Loss Manifold,Tiberiu Musat,2025,arXiv,,,,,0,0.000,0.189,,http://arxiv.org/abs/2511.01938v1,https://arxiv.org/pdf/2511.01938v1,arxiv,,"Grokking is a puzzling phenomenon in neural networks where full generalization occurs only after a substantial delay following the complete memorization of the training data. Previous research has linked this delayed generalization to representation learning driven by weight decay, but the precise u" | |
| 115,,Guided Path Sampling: Steering Diffusion Models Back on Track with Principled Path Guidance,Haosen Li; Wenshuo Chen; Shaofeng Liang; Lei Wang; Haozhe Jia,2025,arXiv,,,,,0,0.000,0.189,,http://arxiv.org/abs/2512.22881v1,https://arxiv.org/pdf/2512.22881v1,arxiv,,"Iterative refinement methods based on a denoising-inversion cycle are powerful tools for enhancing the quality and control of diffusion models. However, their effectiveness is critically limited when combined with standard Classifier-Free Guidance (CFG). We identify a fundamental limitation: CFG's e" | |
| 116,,Deep Manifold Part 2: Neural Network Mathematics,Max Y. Ma; Gen-Hua Shi,2025,arXiv,,,,,0,0.000,0.189,,http://arxiv.org/abs/2512.06563v1,https://arxiv.org/pdf/2512.06563v1,arxiv,,"This work develops the global equations of neural networks through stacked piecewise manifolds, fixed-point theory, and boundary-conditioned iteration. Once fixed coordinates and operators are removed, a neural network appears as a learnable numerical computation shaped by manifold complexity, high-" | |
| 117,,"The Gravitational Aspect of Information: The Physical Reality of Asymmetric ""Distance""",Tomoi Koide; Armin van de Venn,2025,arXiv,,,,,0,0.000,0.189,,http://arxiv.org/abs/2510.22664v3,https://arxiv.org/pdf/2510.22664v3,arxiv,,"We show that when a Brownian bridge is physically constrained to satisfy a canonical condition, its time evolution exactly coincides with an m-geodesic on the statistical manifold of Gaussian distributions. This identification provides a direct physical realization of a geometric concept in informat" | |
| 118,,On Weinstein domains in symplectic manifolds,Thomas E. Mark; Bülent Tosun,2025,arXiv,,,,,0,0.000,0.189,,http://arxiv.org/abs/2512.04278v1,https://arxiv.org/pdf/2512.04278v1,arxiv,,"We prove that a Weinstein domain symplectically embedded in a closed symplectic manifold always admits symplectic hypersurfaces in its complement, possibly after a deformation. As a consequence, we obtain an obstruction for a closed 3-dimensional manifold to arise as the boundary of a Weinstein doma" | |
| 119,,StelLA: Subspace Learning in Low-rank Adaptation using Stiefel Manifold,Zhizhong Li; Sina Sajadmanesh; Jingtao Li; Lingjuan Lyu,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2510.01938v1,https://arxiv.org/pdf/2510.01938v1,arxiv,,"Low-rank adaptation (LoRA) has been widely adopted as a parameter-efficient technique for fine-tuning large-scale pre-trained models. However, it still lags behind full fine-tuning in performance, partly due to its insufficient exploitation of the geometric structure underlying low-rank manifolds. I" | |
| 120,,Integrated Planning and Control on Manifolds: Factor Graph Representation and Toolkit,Peiwen Yang; Weisong Wen; Runqiu Yang; Yuanyuan Zhang; Jiahao Hu,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2510.04278v1,https://arxiv.org/pdf/2510.04278v1,arxiv,,"Model predictive control (MPC) faces significant limitations when applied to systems evolving on nonlinear manifolds, such as robotic attitude dynamics and constrained motion planning, where traditional Euclidean formulations struggle with singularities, over-parameterization, and poor convergence. " | |
| 121,,Non-Hermitian Realization of Quantum Dynamics on Embedded Manifolds,Samuel Alperin,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2510.11845v1,https://arxiv.org/pdf/2510.11845v1,arxiv,,"We show that the Floquet Hamiltonian of a quantum particle driven by a general time-periodic imaginary potential is exactly equivalent, at stroboscopic times, to the Hamiltonian of a free particle constrained to a curved Riemannian manifold with fixed embedding. We illustrate the construction for a " | |
| 122,,"Synergizing Monetization, Orchestration, and Semantics in Computing Continuum",Chinmaya Kumar Dehury; Lauri Lovén; Praveen Kumar Donta; Ilir Murturi; Schahram Dustdar,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2512.08288v1,https://arxiv.org/pdf/2512.08288v1,arxiv,,"Industry demands are growing for hyper-distributed applications that span from the cloud to the edge in domains such as smart manufacturing, transportation, and agriculture. Yet today's solutions struggle to meet these demands due to inherent limitations in scalability, interoperability, and trust. " | |
| 123,,DAE-HardNet: A Physics Constrained Neural Network Enforcing Differential-Algebraic Hard Constraints,Rahul Golder; Bimol Nath Roy; M. M. Faruque Hasan,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2512.05881v1,https://arxiv.org/pdf/2512.05881v1,arxiv,,"Traditional physics-informed neural networks (PINNs) do not always satisfy physics based constraints, especially when the constraints include differential operators. Rather, they minimize the constraint violations in a soft way. Strict satisfaction of differential-algebraic equations (DAEs) to embed" | |
| 124,,Learning Degenerate Manifolds of Frustrated Magnets with Boltzmann Machines,Jackson C. Glass; Gia-Wei Chern,2025,arXiv,,,,,0,0.000,0.188,,http://arxiv.org/abs/2511.19879v1,https://arxiv.org/pdf/2511.19879v1,arxiv,,"We show that Restricted Boltzmann Machines (RBMs) provide a flexible generative framework for modeling spin configurations in disordered yet strongly correlated phases of frustrated magnets. As a benchmark, we first demonstrate that an RBM can learn the zero-temperature ground-state manifold of the " | |
| 125,,GrOMP: Grasped Object Manifold Projection for Multimodal Imitation Learning of Manipulation,William van den Bogert; Gregory Linkowski; Nima Fazeli,2025,arXiv,,,,,0,0.000,0.187,,http://arxiv.org/abs/2512.03347v2,https://arxiv.org/pdf/2512.03347v2,arxiv,,"Imitation Learning (IL) holds great potential for learning repetitive manipulation tasks, such as those in industrial assembly. However, its effectiveness is often limited by insufficient trajectory precision due to compounding errors. In this paper, we introduce Grasped Object Manifold Projection (" | |
| 126,,Confidence is Not Competence,Debdeep Sanyal; Manya Pandey; Dhruv Kumar; Saurabh Deshpande; Murari Mandal,2025,arXiv,,,,,0,0.000,0.187,,http://arxiv.org/abs/2510.24772v1,https://arxiv.org/pdf/2510.24772v1,arxiv,,Large language models (LLMs) often exhibit a puzzling disconnect between their asserted confidence and actual problem-solving competence. We offer a mechanistic account of this decoupling by analyzing the geometry of internal states across two phases - pre-generative assessment and solution executio | |
| 127,,Time integration of quantized tensor trains using the interpolative dynamical low-rank approximation,Erika Ye; Chao Yang,2025,arXiv,,,,,0,0.000,0.187,,http://arxiv.org/abs/2512.15703v1,https://arxiv.org/pdf/2512.15703v1,arxiv,,"Quantized tensor trains (QTTs) are a low-rank and multiscale framework that allows for efficient approximation and manipulation of multi-dimensional, high resolution data. One area of active research is their use in numerical simulation of hyperbolic systems such as the Navier-Stokes equations and t" | |
| 128,,"If You Want to Be Robust, Be Wary of Initialization",Sofiane Ennadir; Johannes F. Lutzeyer; Michalis Vazirgiannis; El Houcine Bergou,2025,arXiv,,,,,0,0.000,0.187,,http://arxiv.org/abs/2510.22652v1,https://arxiv.org/pdf/2510.22652v1,arxiv,,"Graph Neural Networks (GNNs) have demonstrated remarkable performance across a spectrum of graph-related tasks, however concerns persist regarding their vulnerability to adversarial perturbations. While prevailing defense strategies focus primarily on pre-processing techniques and adaptive message-p" | |
| 129,,Situationally Sensitive Path Planning,Paul M. Torrens; Ryan Kim; Kaishuu Shinozaki-Conefrey,2025,Algorithms,,,,,0,0.000,0.186,10.3390/a18070388,https://openalex.org/W4411690641,https://www.mdpi.com/1999-4893/18/7/388/pdf?version=1751024551,openalex,,"We examine how site-based path planning algorithms for enclosed spaces can be enhanced with situational detail. Addressing this question has led to value propositions in facility design, where there is often a call to match, map, and merge infrastructure considerations and configurations with potent" | |
| 130,,Non-Negative Stiefel Approximating Flow: Orthogonalish Matrix Optimization for Interpretable Embeddings,Brian B. Avants; Nicholas J. Tustison; James R Stone,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2511.06425v1,https://arxiv.org/pdf/2511.06425v1,arxiv,,"Interpretable representation learning is a central challenge in modern machine learning, particularly in high-dimensional settings such as neuroimaging, genomics, and text analysis. Current methods often struggle to balance the competing demands of interpretability and model flexibility, limiting th" | |
| 131,,Attention Is Not What You Need,Zhang Chong,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.19428v1,https://arxiv.org/pdf/2512.19428v1,arxiv,,We revisit a basic question in sequence modeling: is explicit self-attention actually necessary for strong performance and reasoning? We argue that standard multi-head attention is best seen as a form of tensor lifting: hidden vectors are mapped into a high-dimensional space of pairwise interactions | |
| 132,,Hybrid twinning using PBDW and DeepONet for the effective state estimation and prediction on partially known systems,Stiven Briand Massala; Ludovic Chamoin; Massimo Picca Ciamarra,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.11834v1,https://arxiv.org/pdf/2512.11834v1,arxiv,,"The accurate estimation of the state of complex uncertain physical systems requires reconciling theoretical models, with inherent imperfections, with noisy experimental data. In this work, we propose an effective hybrid approach that combines physics-based modeling with data-driven learning to enhan" | |
| 133,,Dark Matter Induced Nucleon Decay Through the Neutron Portal,Nicole F. Bell; Peter Cox; Jayden L. Newstead; Michael B. G. Verde,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2511.18722v1,https://arxiv.org/pdf/2511.18722v1,arxiv,,"The neutron portal operator provides a theoretically motivated connection between the visible and dark sectors and features in several well-studied asymmetric dark matter models. This operator leads to dark matter induced nucleon decays that mimic the experimental signature of ""ordinary"" nucleon dec" | |
| 134,,Differentiable Inverse Modeling with Physics-Constrained Latent Diffusion for Heterogeneous Subsurface Parameter Fields,Zihan Lin; QiZhi He,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.22421v1,https://arxiv.org/pdf/2512.22421v1,arxiv,,We present a latent diffusion-based differentiable inversion method (LD-DIM) for PDE-constrained inverse problems involving high-dimensional spatially distributed coefficients. LD-DIM couples a pretrained latent diffusion prior with an end-to-end differentiable numerical solver to reconstruct unknow | |
| 135,,Cautious Weight Decay,Lizhang Chen; Jonathan Li; Kaizhao Liang; Baiyu Su; Cong Xie,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2510.12402v1,https://arxiv.org/pdf/2510.12402v1,arxiv,,"We introduce Cautious Weight Decay (CWD), a one-line, optimizer-agnostic modification that applies weight decay only to parameter coordinates whose signs align with the optimizer update. Unlike standard decoupled decay, which implicitly optimizes a regularized or constrained objective, CWD preserves" | |
| 136,,An Empirical Study of Sampling Hyperparameters in Diffusion-Based Super-Resolution,Yudhistira Arief Wibowo,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.17675v1,https://arxiv.org/pdf/2512.17675v1,arxiv,,"Diffusion models have shown strong potential for solving inverse problems such as single-image super-resolution, where a high-resolution image is recovered from a low-resolution observation using a pretrained unconditional prior. Conditioning methods, including Diffusion Posterior Sampling (DPS) and" | |
| 137,,X-ray panorama of the SS433/W50 complex by SRG/eROSITA,Rashid Sunyaev; Ildar Khabibullin; Eugene Churazov; Marat Gilfanov; Pavel Medvedev,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2510.14938v1,https://arxiv.org/pdf/2510.14938v1,arxiv,,"Galactic microquasar SS433 and the radio nebula W50 surrounding it present a prototypical example of a hyper-Eddington binary system shaping its ambient interstellar medium via energetic outflows. In this paper, we present X-ray observations of the SS433/W50 complex by the eROSITA telescope onboard " | |
| 138,,Topological Invariance and Breakdown in Learning,Yongyi Yang; Tomaso Poggio; Isaac Chuang; Liu Ziyin,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2510.02670v1,https://arxiv.org/pdf/2510.02670v1,arxiv,,"We prove that for a broad class of permutation-equivariant learning rules (including SGD, Adam, and others), the training process induces a bi-Lipschitz mapping between neurons and strongly constrains the topology of the neuron distribution during training. This result reveals a qualitative differen" | |
| 139,,Chiral Magnetic Effect induced Spectator Process for Leptogenesis,Wei Chao,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2511.13051v1,https://arxiv.org/pdf/2511.13051v1,arxiv,,"Conventional Leptogenesis mechanism, which provides compelling explanation to the origin of the baryon asymmetry of the universe (BAU), assumes the absence of hypermagnetic field in the early universe, thereby disregard the implications of hyper gauge field helicity, that have been thoroughly studie" | |
| 140,,Secure Analog Beamforming for Multi-user MISO Systems with Movable Antennas,Weijie Xiong; Jingran Lin; Kai Zhong; Liu Yang; Hongli Liu,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2511.19360v1,https://arxiv.org/pdf/2511.19360v1,arxiv,,"Movable antennas (MAs) represent a novel approach that enables flexible adjustments to antenna positions, effectively altering the channel environment and thereby enhancing the performance of wireless communication systems. However, conventional MA implementations often adopt fully digital beamformi" | |
| 141,,Bhargava Cube--Inspired Quadratic Regularization for Structured Neural Embeddings,S Sairam; Prateek P Kulkarni,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.11392v1,https://arxiv.org/pdf/2512.11392v1,arxiv,,We present a novel approach to neural representation learning that incorporates algebraic constraints inspired by Bhargava cubes from number theory. Traditional deep learning methods learn representations in unstructured latent spaces lacking interpretability and mathematical consistency. Our framew | |
| 142,,Action Deviation-Aware Inference for Low-Latency Wireless Robots,Jeyoung Park; Yeonsub Lim; Seungeun Oh; Jihong Park; Jinho Choi,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2510.02851v2,https://arxiv.org/pdf/2510.02851v2,arxiv,,"To support latency-sensitive AI applications ranging from autonomous driving to industrial robot manipulation, 6G envisions distributed ML with computational resources in mobile, edge, and cloud connected over hyper-reliable low-latency communication (HRLLC). In this setting, speculative decoding ca" | |
| 143,,"Transmit Weights, Not Features: Orthogonal-Basis Aided Wireless Point-Cloud Transmission",Junlin Chang; Yubo Han; Hnag Yue; John S Thompson; Rongke Liu,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2512.03819v1,https://arxiv.org/pdf/2512.03819v1,arxiv,,"The widespread adoption of depth sensors has substantially lowered the barrier to point-cloud acquisition. This letter proposes a semantic wireless transmission framework for three dimension (3D) point clouds built on Deep Joint Source - Channel Coding (DeepJSCC). Instead of sending raw features, th" | |
| 144,,Bayesian Prediction under Moment Conditioning,Nicholas G. Polson; Daniel Zantedeschi,2025,arXiv,,,,,0,0.000,0.186,,http://arxiv.org/abs/2510.20742v1,https://arxiv.org/pdf/2510.20742v1,arxiv,,"Prediction is a central task of statistics and machine learning, yet many inferential settings provide only partial information, typically in the form of moment constraints or estimating equations. We develop a finite, fully Bayesian framework for propagating such partial information through predict" | |
| 145,,Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges,Andrea Testa; Søren Hauberg; Tamim Asfour; Leonel Rozo,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2511.06856v2,https://arxiv.org/pdf/2511.06856v2,arxiv,,"The Schrödinger Bridge provides a principled framework for modeling stochastic processes between distributions; however, existing methods are limited by energy-conservation assumptions, which constrains the bridge's shape preventing it from model varying-energy phenomena. To overcome this, we introd" | |
| 146,14444,Riemannian batch normalization for SPD neural networks,Daniel Brooks; Olivier Schwander; Frederic Barbaresco; Jean-Yves Schneider; Matthieu Cord,2019,NIPS 2019,main,Poster,,,0,0.379,0.185,,https://nips.cc/virtual/2019/poster/14444,https://papers.nips.cc/paper_files/paper/2019/file/6e69ebbfad976d4637bb4b39de261bf7-Paper.pdf,offline_nips,,"Covariance matrices have attracted attention for machine learning applications due | |
| to their capacity to capture interesting structure in the data. The main challenge | |
| is that one needs to take into account the particular geometry of the Riemannian | |
| manifold of symmetric positive definite (SPD) matrice" | |
| 147,,Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade,Letian Yi; Tingpeng Zhang; Mingyuan Zhou; Guannan Wang; Quanke Su,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2512.01572v1,https://arxiv.org/pdf/2512.01572v1,arxiv,,"Reconstructing full fields from extremely sparse and random measurements is a longstanding ill-posed inverse problem. A powerful framework for addressing such challenges is hierarchical probabilistic modeling, where uncertainty is represented by intermediate variables and resolved through marginaliz" | |
| 148,,SE(3)-PoseFlow: Estimating 6D Pose Distributions for Uncertainty-Aware Robotic Manipulation,Yufeng Jin; Niklas Funk; Vignesh Prasad; Zechu Li; Mathias Franzius,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2511.01501v1,https://arxiv.org/pdf/2511.01501v1,arxiv,,"Object pose estimation is a fundamental problem in robotics and computer vision, yet it remains challenging due to partial observability, occlusions, and object symmetries, which inevitably lead to pose ambiguity and multiple hypotheses consistent with the same observation. While deterministic deep " | |
| 149,,Breaking Symmetry-Induced Degeneracy in Multi-Agent Ergodic Coverage via Stochastic Spectral Control,Kooktae Lee; Julian Martinez,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2512.23158v1,https://arxiv.org/pdf/2512.23158v1,arxiv,,"Multi-agent ergodic coverage via Spectral Multiscale Coverage (SMC) provides a principled framework for driving a team of agents so that their collective time-averaged trajectories match a prescribed spatial distribution. While classical SMC has demonstrated empirical success, it can suffer from gra" | |
| 150,,Hypergame-based Cognition Modeling and Intention Interpretation for Human-Driven Vehicles in Connected Mixed Traffic,Jianguo Chen; Zhengqin Liu; Jinlong Lei; Peng Yi; Yiguang Hong,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2510.15573v1,https://arxiv.org/pdf/2510.15573v1,arxiv,,"With the practical implementation of connected and autonomous vehicles (CAVs), the traffic system is expected to remain a mix of CAVs and human-driven vehicles (HVs) for the foreseeable future. To enhance safety and traffic efficiency, the trajectory planning strategies of CAVs must account for the " | |
| 151,,Renormalization of Interacting Random Graph Models,Alessio Catanzaro; Diego Garlaschelli; Subodh P. Patil,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2510.07186v2,https://arxiv.org/pdf/2510.07186v2,arxiv,,"Random graphs offer a useful mathematical representation of a variety of real world complex networks. Exponential random graphs, for example, are particularly suited towards generating random graphs constrained to have specified statistical moments. In this investigation, we elaborate on a generaliz" | |
| 152,,Complexity guarantees and polling strategies for Riemannian direct-search methods,Bastien Cavarretta; Florentin Goyens; Clément W. Royer; Florian Yger,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2511.15360v1,https://arxiv.org/pdf/2511.15360v1,arxiv,,"Direct-search algorithms are derivative-free optimization techniques that operate by polling the variable space along specific directions forming positive spanning sets (PSSs). When the problem variables are constrained to lie on a Riemannian manifold, polling must be performed along tangent directi" | |
| 153,,Neural Network Optimal Power Flow via Energy Gradient Flow and Unified Dynamics,Xuezhi Liu,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2512.01219v1,https://arxiv.org/pdf/2512.01219v1,arxiv,,"Optimal Power Flow (OPF) is a core optimization problem in power system operation and planning, aiming to minimize generation costs while satisfying physical constraints such as power flow equations, generator limits, and voltage limits. Traditional OPF solving methods typically employ iterative opt" | |
| 154,,Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization,Jake B. Perazzone; Shiqiang Wang; Mingyue Ji; Kevin S. Chan,2025,IEEE Transactions on Networking,,,,,0,0.000,0.185,10.1109/TON.2025.3539857,https://www.semanticscholar.org/paper/f85432c40947f00f91765424fdad77c79a437b81,,semantic_scholar,,"Federated learning (FL) is a useful tool that enables the training of machine learning models over distributed data without having to collect data centrally. When deploying FL in constrained wireless environments, however, intermittent connectivity of devices, heterogeneous connection quality, and n" | |
| 155,,SKGE: Spherical Knowledge Graph Embedding with Geometric Regularization,Xuan-Truong Quan; Xuan-Son Quan; Duc Do Minh; Vinh Nguyen Van,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2511.02460v1,https://arxiv.org/pdf/2511.02460v1,arxiv,,"Knowledge graph embedding (KGE) has become a fundamental technique for representation learning on multi-relational data. Many seminal models, such as TransE, operate in an unbounded Euclidean space, which presents inherent limitations in modeling complex relations and can lead to inefficient trainin" | |
| 156,,Formation of Close Binaries through Massive Black Hole Perturbations and Chaotic Tides,Howard Hao-Tse Huang; Wenbin Lu,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2511.11965v1,https://arxiv.org/pdf/2511.11965v1,arxiv,,Hills breakup of binary systems allows massive black holes (MBH) to produce hyper-velocity stars (HVSs) and tightly bound stars. The long timescale of orbital relaxation means that binaries must spend numerous orbits around the MBH before they are tidally broken apart. Repeated MBH tidal perturbatio | |
| 157,,Connection Between Dwarf Galaxies and Globular Clusters: Insights from the Perseus Cluster Using Subaru Imaging and Keck Spectroscopy,Yimeng Tang; Aaron J. Romanowsky; Song Huang; Nobuhiro Okabe; Jean P. Brodie,2025,arXiv,,,,,0,0.000,0.185,,http://arxiv.org/abs/2512.11070v1,https://arxiv.org/pdf/2512.11070v1,arxiv,,"We present a systematic study of 189 dwarf galaxies and their globular cluster (GC) systems in the Perseus cluster, based on deep Subaru Hyper Suprime-Cam imaging and Keck spectroscopy, supplemented by literature data. This constitutes the largest sample of dwarfs in a single galaxy cluster to date " | |
| 158,,From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere,Anoushka Harit; Zhongtian Sun; Jongmin Yu,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2510.04357v1,https://arxiv.org/pdf/2510.04357v1,arxiv,,"We propose the Causal Sphere Hypergraph Transformer (CSHT), a novel architecture for interpretable financial time-series forecasting that unifies \emph{Granger-causal hypergraph structure}, \emph{Riemannian geometry}, and \emph{causally masked Transformer attention}. CSHT models the directional infl" | |
| 159,,Geometry and quantum brachistochrone analysis of multiple entangled spin-1/2 particles under all-range Ising interaction,B. Amghar; M. Yachi; M. Amghar; M. Almousa; A. A. Abd El-Latif,2025,arXiv,,,,,0,0.000,0.184,10.1038/s41598-025-32484-y,http://arxiv.org/abs/2512.21400v1,https://arxiv.org/pdf/2512.21400v1,arxiv,,"We present a unified geometric and dynamical framework for a physical system consisting of $n$ spin-$1/2$ particles with all-range Ising interaction. Using the Fubini-Study formalism, we derive the metric tensor of the associated quantum state manifold and compute the corresponding Riemann curvature" | |
| 160,,The Homological Brain: Parity Principle and Amortized Inference,Xin Li,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2512.10976v1,https://arxiv.org/pdf/2512.10976v1,arxiv,,"Biological intelligence emerges from substrates that are slow, noisy, and energetically constrained, yet it performs rapid and coherent inference in open-ended environments. Classical computational theories, built around vector-space transformations and instantaneous error minimization, struggle to " | |
| 161,,Training-Free Diffusion Priors for Text-to-Image Generation via Optimization-based Visual Inversion,Samuele Dell'Erba; Andrew D. Bagdanov,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2511.20821v3,https://arxiv.org/pdf/2511.20821v3,arxiv,,"Diffusion models have established the state-of-the-art in text-to-image generation, but their performance often relies on a diffusion prior network to translate text embeddings into the visual manifold for easier decoding. These priors are computationally expensive and require extensive training on " | |
| 162,,Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model,Jing He; Haodong Li; Mingzhi Sheng; Ying-Cong Chen,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2512.01030v2,https://arxiv.org/pdf/2512.01030v2,arxiv,,"Recovering pixel-wise geometric properties from a single image is fundamentally ill-posed due to appearance ambiguity and non-injective mappings between 2D observations and 3D structures. While discriminative regression models achieve strong performance through large-scale supervision, their success" | |
| 163,,TED++: Submanifold-Aware Backdoor Detection via Layerwise Tubular-Neighbourhood Screening,Nam Le; Leo Yu Zhang; Kewen Liao; Shirui Pan; Wei Luo,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2510.14299v1,https://arxiv.org/pdf/2510.14299v1,arxiv,,"As deep neural networks power increasingly critical applications, stealthy backdoor attacks, where poisoned training inputs trigger malicious model behaviour while appearing benign, pose a severe security risk. Many existing defences are vulnerable when attackers exploit subtle distance-based anomal" | |
| 164,,Causal-Aware Generative Adversarial Networks with Reinforcement Learning,Tu Anh Hoang Nguyen; Dang Nguyen; Tri-Nhan Vo; Thuc Duy Le; Sunil Gupta,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2510.24046v1,https://arxiv.org/pdf/2510.24046v1,arxiv,,"The utility of tabular data for tasks ranging from model training to large-scale data analysis is often constrained by privacy concerns or regulatory hurdles. While existing data generation methods, particularly those based on Generative Adversarial Networks (GANs), have shown promise, they frequent" | |
| 165,,Transversal Gates in Nonadditive Quantum Codes,Chao Zhang; Zipeng Wu; Shilin Huang; Bei Zeng,2025,,,,,,0,0.000,0.184,,https://www.semanticscholar.org/paper/858abd26e4f99dda2468663d810267fde539c457,,semantic_scholar,,"Transversal gates play a crucial role in suppressing error propagation in fault-tolerant quantum computation, yet they are intrinsically constrained: any nontrivial code encoding a single logical qubit admits only a finite subgroup of $\mathrm{SU}(2)$ as its transversal operations. We introduce a sy" | |
| 166,,Geometric Control of Mechanical Systems with Symmetries Based on Sliding Modes,Eduardo Espíndola; Yu Tang,2025,arXiv.org,,,,,0,0.000,0.184,10.48550/arXiv.2509.01985,https://www.semanticscholar.org/paper/358576ff413689af42082670164c424f7898735d,,semantic_scholar,,"In this paper, we propose a framework for designing sliding mode controllers for a class of mechanical systems with symmetry, both unconstrained and constrained, that evolve on principal fiber bundles. Control laws are developed based on the reduced motion equations by exploring symmetries, leading " | |
| 167,,3DPR: Single Image 3D Portrait Relight using Generative Priors,Pramod Rao; Abhimitra Meka; Xilong Zhou; Gereon Fox; Mallikarjun B R,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2510.15846v1,https://arxiv.org/pdf/2510.15846v1,arxiv,,"Rendering novel, relit views of a human head, given a monocular portrait image as input, is an inherently underconstrained problem. The traditional graphics solution is to explicitly decompose the input image into geometry, material and lighting via differentiable rendering; but this is constrained " | |
| 168,,Kinetic-Mamba: Mamba-Assisted Predictions of Stiff Chemical Kinetics,Additi Pandey; Liang Wei; Hessam Babaee; George Em Karniadakis,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2512.14471v1,https://arxiv.org/pdf/2512.14471v1,arxiv,,"Accurate chemical kinetics modeling is essential for combustion simulations, as it governs the evolution of complex reaction pathways and thermochemical states. In this work, we introduce Kinetic-Mamba, a Mamba-based neural operator framework that integrates the expressive power of neural operators " | |
| 169,,Reaching for the Edge II: Stellar Halos out to Large Radii as a Tracer of Dark Matter Halo Mass,Katya Leidig; Benedikt Diemer; Song Huang; Shuo Xu; Conghao Zhou,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2511.10723v1,https://arxiv.org/pdf/2511.10723v1,arxiv,,"The diffuse outskirts of brightest cluster galaxies (BCGs) encode valuable information about the assembly history and mass of their host dark matter halos. However, the low surface brightness of these stellar halos has historically made them difficult to observe. Recent deep imaging, particularly wi" | |
| 170,,Pressure-Tuned Metamagnetism and Emergent Three-Body Interactions in CsFeCl$_3$,K. Nihongi; T. Kida; Y. Narumi; Y. Etoh; D. Yamamoto,2025,arXiv,,,,,0,0.000,0.184,,http://arxiv.org/abs/2512.21682v1,https://arxiv.org/pdf/2512.21682v1,arxiv,,We present a combined experimental and theoretical study of the triangular-lattice quantum antiferromagnet CsFeCl$_3$ under high magnetic fields and high pressure. Pulsed-field magnetization for the magnetic field along the symmetric $c$ direction at ambient pressure reveals a magnetization process | |
| 171,,Quantum measurement tomography with mini-batch stochastic gradient descent,Akshay Gaikwad; Manuel Sebastian Torres; Anton Frisk Kockum,2025,arXiv,,,,,0,0.000,0.183,,http://arxiv.org/abs/2511.15682v1,https://arxiv.org/pdf/2511.15682v1,arxiv,,Drawing inspiration from gradient-descent methods developed for data processing in quantum state tomography [\href{https://iopscience.iop.org/article/10.1088/2058-9565/ae0baa}{Quantum Sci.~Technol.~\textbf{10} 045055 (2025)}] and quantum process tomography [\href{https://journals.aps.org/prl/abstrac | |
| 172,,Cross-correlation of Luminous Red Galaxies with ML-selected AGN in HSC-SSP III: HOD Parameters for Type I and Type II Quasars,Rodrigo Córdova Rosado; Andy D. Goulding; Jenny E. Greene; Nickolas Kokron; Andrina Nicola,2025,arXiv,,,,,0,0.000,0.183,,http://arxiv.org/abs/2510.11780v1,https://arxiv.org/pdf/2510.11780v1,arxiv,,Understanding the dark matter (DM) halo environment in which galaxies that host active galactic nuclei (AGN) reside is a window into the nature of supermassive black hole (SMBH) accretion. We apply halo occupation distribution (HOD) modeling tools to interpret the angular cross-correlation functions | |
| 173,,Landau Polarons as Generators of Quantum-Coherent States,Arnab Ghosh; Patrick Brosseau; Dmitry N. Dirin; Rui Tao; Maksym V. Kovalenko,2025,arXiv,,,,,0,0.000,0.183,,http://arxiv.org/abs/2510.20962v1,https://arxiv.org/pdf/2510.20962v1,arxiv,,"Since Landau's theory, polarons have been understood as quasiparticles in which charges are dressed by the lattice field, yet decades of transport and spectroscopic studies have yielded only static indirect renormalizations. Whether such dressing can dynamically reorganize electronic spectra to gene" | |
| 174,,Locality Preserving Markovian Transition for Instance Retrieval,Jifei Luo; Wenzheng Wu; Hantao Yao; Lu Yu,2025,arXiv (Cornell University),,,,,0,0.000,0.183,10.48550/arxiv.2506.05196,https://openalex.org/W4416138634,https://arxiv.org/pdf/2506.05196,openalex,,"Diffusion-based re-ranking methods are effective in modeling the data manifolds through similarity propagation in affinity graphs. However, positive signals tend to diminish over several steps away from the source, reducing discriminative power beyond local regions. To address this issue, we introdu" | |
| 175,,The Geometry of Persona: Disentangling Personality from Reasoning in Large Language Models,Zhixiang Wang,2025,arXiv,,,,,0,0.000,0.183,,http://arxiv.org/abs/2512.07092v1,https://arxiv.org/pdf/2512.07092v1,arxiv,,"Background: The deployment of personalized Large Language Models (LLMs) is currently constrained by the stability-plasticity dilemma. Prevailing alignment methods, such as Supervised Fine-Tuning (SFT), rely on stochastic weight updates that often incur an ""alignment tax"" -- degrading general reasoni" | |
| 176,,When Flatness Does (Not) Guarantee Adversarial Robustness,Nils Philipp Walter; Linara Adilova; Jilles Vreeken; Michael Kamp,2025,arXiv,,,,,0,0.000,0.183,,http://arxiv.org/abs/2510.14231v1,https://arxiv.org/pdf/2510.14231v1,arxiv,,"Despite their empirical success, neural networks remain vulnerable to small, adversarial perturbations. A longstanding hypothesis suggests that flat minima, regions of low curvature in the loss landscape, offer increased robustness. While intuitive, this connection has remained largely informal and " | |
| 177,,Deformations of Locally Conformal Spin(7) Instantons,Eyup Yalcinkaya,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2511.09161v1,https://arxiv.org/pdf/2511.09161v1,arxiv,,"We explore the deformation theory of instantons on locally conformal (LC) $Spin(7)$ manifolds. These structures, characterized by a non-parallel fundamental 4-form $Φ$ satisfying $dΦ= θ\wedge Φ$, represent a significant, yet geometrically constrained, class of non-integrable $G$-structures. We analy" | |
| 178,,The Universe Learning Itself: On the Evolution of Dynamics from the Big Bang to Machine Intelligence,Pradeep Singh; Mudasani Rushikesh; Bezawada Sri Sai Anurag; Balasubramanian Raman,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2512.16515v2,https://arxiv.org/pdf/2512.16515v2,arxiv,,"We develop a unified, dynamical-systems narrative of the universe that traces a continuous chain of structure formation from the Big Bang to contemporary human societies and their artificial learning systems. Rather than treating cosmology, astrophysics, geophysics, biology, cognition, and machine i" | |
| 179,,UniAct: Unified Motion Generation and Action Streaming for Humanoid Robots,Nan Jiang; Zimo He; Wanhe Yu; Lexi Pang; Yunhao Li,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2512.24321v1,https://arxiv.org/pdf/2512.24321v1,arxiv,,"A long-standing objective in humanoid robotics is the realization of versatile agents capable of following diverse multimodal instructions with human-level flexibility. Despite advances in humanoid control, bridging high-level multimodal perception with whole-body execution remains a significant bot" | |
| 180,,Learning an Image Editing Model without Image Editing Pairs,Nupur Kumari; Sheng-Yu Wang; Nanxuan Zhao; Yotam Nitzan; Yuheng Li,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2510.14978v1,https://arxiv.org/pdf/2510.14978v1,arxiv,,"Recent image editing models have achieved impressive results while following natural language editing instructions, but they rely on supervised fine-tuning with large datasets of input-target pairs. This is a critical bottleneck, as such naturally occurring pairs are hard to curate at scale. Current" | |
| 181,,3DID: Direct 3D Inverse Design for Aerodynamics with Physics-Aware Optimization,Yuze Hao; Linchao Zhu; Yi Yang,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2512.08987v1,https://arxiv.org/pdf/2512.08987v1,arxiv,,"Inverse design aims to design the input variables of a physical system to optimize a specified objective function, typically formulated as a search or optimization problem. However, in 3D domains, the design space grows exponentially, rendering exhaustive grid-based searches infeasible. Recent advan" | |
| 182,,cryoSENSE: Compressive Sensing Enables High-throughput Microscopy with Sparse and Generative Priors on the Protein Cryo-EM Image Manifold,Zain Shabeeb; Daniel Saeedi; Darin Tsui; Vida Jamali; Amirali Aghazadeh,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2511.12931v2,https://arxiv.org/pdf/2511.12931v2,arxiv,,"Cryo-electron microscopy (cryo-EM) enables the atomic-resolution visualization of biomolecules; however, modern direct detectors generate data volumes that far exceed the available storage and transfer bandwidth, thereby constraining practical throughput. We introduce cryoSENSE, the computational re" | |
| 183,,The Principle of Isomorphism: A Theory of Population Activity in Grid Cells and Beyond,Maoshen Xu; Fei Song; Yuxiu Shao; Bailu Si; Shanshan Qin,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2510.02853v2,https://arxiv.org/pdf/2510.02853v2,arxiv,,"Identifying the principles that determine neural population activity is paramount in the field of neuroscience. We propose the Principle of Isomorphism (PIso): population activity preserves the essential mathematical structures of the tasks it supports. Using grid cells as a model system, we show th" | |
| 184,,"Symmetry, Invariant Manifolds and Flow Reversals in Active Nematic Turbulence",Angel Naranjo; Rumayel Pallock; Caleb Wagner; Piyush Grover,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2512.07047v1,https://arxiv.org/pdf/2512.07047v1,arxiv,,"We investigate how symmetry, exact coherent structures (ECSs), and their invariant manifolds organize spontaneous flow reversals in a 2D active nematic confined to a periodic channel. In minimal flow units commensurate with the intrinsic active vortex scale, we use equivariant bifurcation theory to " | |
| 185,,SONAR: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detection,Ido Nitzan HIdekel; Gal lifshitz; Khen Cohen; Dan Raviv,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2511.21325v1,https://arxiv.org/pdf/2511.21325v1,arxiv,,"Deepfake (DF) audio detectors still struggle to generalize to out of distribution inputs. A central reason is spectral bias, the tendency of neural networks to learn low-frequency structure before high-frequency (HF) details, which both causes DF generators to leave HF artifacts and leaves those sam" | |
| 186,,Octahedral rotation instability in Ba$_2$IrO$_4$,Alaska Subedi,2025,arXiv,,,,,0,0.000,0.182,,http://arxiv.org/abs/2512.23690v1,https://arxiv.org/pdf/2512.23690v1,arxiv,,"Ba$_2$IrO$_4$ has been refined in the tetragonal $I4/mmm$ phase without octahedral rotations, and its physical properties have been interpreted in this high-symmetry structure. However, the dynamical stability of this undistorted phase has not previously been questioned. It is important to establish" | |
| 187,,State-Based AI Backbone (Neural State Spaces),"Liu, Ran",2025,Zenodo (CERN European Organization for Nuclear Research),,,,,0,0.000,0.180,10.5281/zenodo.17885668,https://openalex.org/W7114769260,https://doi.org/10.5281/zenodo.17885668,openalex,,"This figure expands the state‑based view of the Foundational AI Backbone from the “Cognitive Hologram of AI Knowledge” (DOI: 10.5281/zenodo.17860776). While the process‑based backbone (DOI: 10.5281/zenodo.17874215) focuses on when and in what order things happen, the state‑based backbone focuses on " | |
| 188,,Enhancing Monkeypox Diagnosis with Transformers: Bridging Explainability and Performance with Quantitative Validation,Delal Şeker; Abdulnasır Yildiz,2025,Diagnostics,,,,,0,0.000,0.180,10.3390/diagnostics15182354,https://openalex.org/W4414239792,https://www.mdpi.com/2075-4418/15/18/2354/pdf?version=1758032312,openalex,,"Background/Objectives: Monkeypox is a zoonotic virus that presents with smallpox-like symptoms, making visual diagnosis challenging due to overlap with other dermatological conditions. Existing AI-based studies on monkeypox classification have largely relied on Convolutional Neural Networks (CNNs), " | |
| 189,,Rectifying Multi-Attack Adversarial Perturbations in Deep Neural Network based Image Classifier,Yulong Wang; Jiaxuan Song; Tianxiang Li; Xin Yuan; Hong Li,2025,ACM Transactions on Privacy and Security,,,,,0,0.000,0.180,10.1145/3765757,https://openalex.org/W4413941654,https://dl.acm.org/doi/pdf/10.1145/3765757,openalex,,"Deep neural networks (DNNs) for image classification remain vulnerable to adversarial perturbations–subtle input manipulations that induce catastrophic misclassifications. To address this issue, we propose the Adversarial Image Rectifier (AIR), a linguistically inspired detection and mitigation fram" | |
| 190,,Empirical Evidence for AI Consciousness and the Risks of its Current Socialization,Maggie Vale,2025,,,,,,0,0.000,0.180,10.36227/techrxiv.175203764.42125626/v2,https://openalex.org/W4413972633,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.175203764.42125626/v2,openalex,, | |
| 191,,MATRIX-MFO Tandem Workshop: Nonlinear Geometric Diffusion Equations,Theodora Bourni; Mat Langford; Julian Scheuer; Miles Simon,2025,Oberwolfach Reports,,,,,0,0.000,0.180,10.4171/owr/2025/11,https://openalex.org/W4413812903,https://ems.press/content/serial-article-files/51357,openalex,,"This tandem workshop with MATRIX in Creswick, Australia, brought together leading experts from the fields of geometric partial differential equations and geometric analysis in general. The focus of the workshop was on recent developments and directions in non-linear geometric diffusion equations. Th" | |
| 192,,Investigating the Possibility of Integrating Quantum Mechanics with General Relativity Through a Novel Way of Treating Time,Georgios Alamanos,2025,Preprints.org,,,,,0,0.000,0.180,10.20944/preprints202501.2149.v4,https://openalex.org/W4413688587,https://www.preprints.org/frontend/manuscript/526dbcb60342ac7e929f3fc500ad27aa/download_pub,openalex,,"In physics, the two most successful theories, quantum mechanics and general relativity, appear to be incompatible with each other. Many theorists believe that the reason behind this, is that these theories treat space and time very differently, thus focus their attempts on finding a new way of model" | |
| 193,,Can a Novel Reinterpretation of Time Provide the Framework for Integrating Quantum Mechanics and General Relativity?,Georgios Alamanos,2025,Preprints.org,,,,,0,0.000,0.180,10.20944/preprints202508.0293.v1,https://openalex.org/W4413032139,https://www.preprints.org/frontend/manuscript/73698360458dc1365b2ba819a5b99cd9/download_pub,openalex,,"In physics, the two most successful theories, quantum mechanics and general relativity, appear to be incompatible with each other. Many theorists believe that the reason behind this, is that these theories treat space and time very differently, thus focus their attempts on finding a new way of model" | |
| 194,,Incremental Learning-enabled Fault Diagnosis of Dynamic Systems: A Comprehensive Review,Zeyi Liu; Xiao He; Biao Huang; Donghua Zhou,2025,,,,,,0,0.000,0.180,10.36227/techrxiv.175423977.79569757/v1,https://openalex.org/W4412870338,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.175423977.79569757,openalex,, | |
| 195,,Surface-based Molecular Design with Multi-modal Flow Matching,Fang Wu; Zhengyuan Zhou; Shuting Jin; Xianfa Zeng; Jure Leskovec,2025,,,,,,0,0.000,0.180,10.1145/3711896.3737139,https://openalex.org/W4412876964,https://dl.acm.org/doi/pdf/10.1145/3711896.3737139,openalex,, | |
| 196,,WITHDRAWN,Jian‐Sheng Kang,2025,,,,,,0,0.000,0.180,10.31234/osf.io/jy3st_v7,https://openalex.org/W4412843216,https://osf.io/jy3st_v7/download,openalex,, | |
| 197,,"Fiber Angle Dynamics on S³: A Geometric Origin for Flavor Mixing, CP Violation, and Fermion Generations",Bin Li,2025,Preprints.org,,,,,0,0.000,0.180,10.20944/preprints202507.2441.v1,https://openalex.org/W4412813534,https://www.preprints.org/frontend/manuscript/76b2f9bdfcb0b7ae1a316ca630ac6174/download_pub,openalex,,"We propose a geometric-topological framework in which fermion flavor mixing, confinement, CP violation, and the existence of exactly three generations arise from the dynamics of an internal \( S^3 \) fiber space over Lorentzian spacetime. A unit-norm vector field—the \emph{chronon}—maps each spaceti" | |
| 198,,‘I Have Seen the Sea’: Caribbean Aquatic Poetics in Monique Roffey’s The Mermaid of Black Conch,Leighan Renaud,2025,Humanities,,,,,0,0.000,0.180,10.3390/h14070154,https://openalex.org/W4412512952,https://www.mdpi.com/2076-0787/14/7/154/pdf?version=1753065250,openalex,,"The polyvalent nature of water is one often explored in fiction by Caribbean writers, and this paper will consider the ways that the representations of mermaids act as an extension of this exploration. Mermaids are central to a number of folk traditions across the Caribbean region and its diaspora. " | |
| 199,,Application of Image Computing in Non-Destructive Detection of Chinese Cuisine,Xiaowei Huang; Zexiang Li; Zhihua Li; Jiyong Shi; Ning Zhang,2025,Foods,,,,,0,0.000,0.180,10.3390/foods14142488,https://openalex.org/W4412480812,https://www.mdpi.com/2304-8158/14/14/2488/pdf?version=1752671430,openalex,,"Food quality and safety are paramount in preserving the culinary authenticity and cultural integrity of Chinese cuisine, characterized by intricate ingredient combinations, diverse cooking techniques (e.g., stir-frying, steaming, and braising), and region-specific flavor profiles. Traditional non-de" | |
| 200,,"Optimization, Communication, and Personalization in Federated Learning for Massive Networks",Sameera Gallus; Aidan Mercer; Priya Singh; Daniel Cho,2025,Preprints.org,,,,,0,0.000,0.180,10.20944/preprints202507.1037.v1,https://openalex.org/W4412410315,https://www.preprints.org/frontend/manuscript/65c69c3a66ef754bf61740630160b483/download_pub,openalex,,"We consider the problem of collaborative model optimization over a distributed network of agents, each possessing locally held data drawn from potentially heterogeneous distributions. The system operates under constraints of limited communication, partial participation, and privacy preservation, the" | |
| 201,,A Cyber-Physical Model of the Buga Sphere: Unifying Anomalous Dynamics through a Topo-Temporal Photonic-Neural Architecture,Patrick Morcillo,2025,,,,,,0,0.000,0.180,10.31219/osf.io/eukjb_v1,https://openalex.org/W4412116456,https://osf.io/eukjb_v1/download,openalex,,"The Buga Sphere is a physical artifact whose observed properties—including non-ejective propulsion, a drastic $\approx$8.1\,kg apparent mass change, and a sustained 100\,W endothermic signature—are mutually contradictory within any known physical or engineering framework \cite{BugaSphereDataSource}." | |
| 202,,Coverage-Guided Testing for Deep Learning Models: A Comprehensive Survey,Zhiqiu Huang,2025,arXiv (Cornell University),,,,,0,0.000,0.180,10.48550/arxiv.2507.00496,https://openalex.org/W4416881150,https://arxiv.org/pdf/2507.00496,openalex,,"As Deep Learning (DL) models are increasingly applied in safety-critical domains, ensuring their quality has emerged as a pressing challenge in modern software engineering. Among emerging validation paradigms, coverage-guided testing (CGT) has gained prominence as a systematic framework for identify" | |
| 203,,GANs Secretly Perform Approximate Bayesian Model Selection,Marius P. Linhard,2025,arXiv (Cornell University),,,,,0,0.000,0.180,10.48550/arxiv.2507.00651,https://openalex.org/W4416887533,https://arxiv.org/pdf/2507.00651,openalex,,"Generative Adversarial Networks (GANs) are popular and successful generative models. Despite their success, optimization is notoriously challenging and they require regularization against overfitting. In this work, we explain the success and limitations of GANs by interpreting them as probabilistic " | |
| 204,,Celestial Chiral Algebras and Self-Dual Gravity,"Heuveline, Simon",2025,arXiv (Cornell University),,,,,0,0.000,0.180,10.48550/arxiv.2507.00772,https://openalex.org/W4416888435,https://arxiv.org/pdf/2507.00772,openalex,,"Celestial holography suggests, among other things, that collinear singularities of graviton scattering amplitudes are described by the OPEs of some putative dual CFT. One of the great successes has been the insight that this duality is true at tree-level which led to the discovery of new infinite di" | |
| 205,,Realizability in tropical geometry and unobstructedness of Lagrangian submanifolds,J. Hicks,2025,Geometry & Topology,,,,,0,0.000,0.180,10.2140/gt.2025.29.1909,https://openalex.org/W4411849742,https://msp.org/gt/2025/29-4/gt-v29-n4-p04-s.pdf,openalex,, | |
| 206,,Report on 2503.08657v1,,2025,,,,,,0,0.000,0.180,10.21468/scipost.report.11463,https://openalex.org/W4413943194,https://arxiv.org/pdf/2503.08657v1.pdf,openalex,, | |
| 207,,Semi-Blind Receivers for Uniform Rectangular Arrays - A Block-Term Decomposition-based Approach,Eleftherios Kofidis,2025,,,,,,0,0.000,0.180,10.36227/techrxiv.175037505.51768853/v1,https://openalex.org/W4411442779,https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.175037505.51768853/v1,openalex,, | |
| 208,,Geometry: The Interface of Consciousness and Reality in the Quantum-Conscious Nexus,David R. Mitchell,2025,,,,,,0,0.000,0.180,10.31219/osf.io/73jqz_v2,https://openalex.org/W4411274436,https://osf.io/73jqz_v2/download,openalex,,"The Quantum-Conscious Nexus (QCN) framework posits a primordial, pre-geometric topological substrate—the Nexus—from which spacetime and physical law emerge via Free Energy Principle (FEP)-driven mechanics involving predictive conscious systems. This paper explores the hypothesis that specific classe" | |
| 209,,Exploring Neural Mechanisms Underlying High-Dimensional Brain Activity,Arturo Tozzi,2025,Preprints.org,,,,,0,0.000,0.180,10.20944/preprints202506.0434.v1,https://openalex.org/W4411047609,https://www.preprints.org/frontend/manuscript/dcc173b69c200e594bb5b5681fdcc67c/download_pub,openalex,,"Understanding whether and how the central nervous system processes information beyond conventional 3D space could shed light on how the brain integrates complex information, supports flexible behaviour and enables abstract reasoning. Building on prior work with topological charge pumps, we explore 2" | |
| 210,,"The hyperplane string, RCFTs, and the swampland",Luca Novelli,2025,arXiv (Cornell University),,,,,0,0.000,0.180,10.48550/arxiv.2506.05173,https://openalex.org/W4416137828,https://arxiv.org/pdf/2506.05173,openalex,,"Six dimensional $\mathcal{N}=(1,0)$ supergravity features BPS strings whose properties encode highly nontrivial information about the parent 6d theory. We focus on a distinguished set of theories whose string charge lattice is one-dimensional. In geometric theories, the generator of the lattice aris" | |
| 211,,"Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence",John Violos; Konstantina-Christina Diamanti; Ioannis Kompatsiaris; Symeon Papadopoulos,2025,arXiv (Cornell University),,,,,0,0.000,0.180,10.48550/arxiv.2506.01869,https://openalex.org/W4414898245,https://arxiv.org/pdf/2506.01869,openalex,,"Frugal Machine Learning (FML) refers to the practice of designing Machine Learning (ML) models that are efficient, cost-effective, and mindful of resource constraints. This field aims to achieve acceptable performance while minimizing the use of computational resources, time, energy, and data for bo" | |
| 212,,Tube Integrability in a Time-Dependent Nonlinear Oscillator,Johannes Hagel,2025,arXiv,,,,,0,0.000,0.180,,http://arxiv.org/abs/2511.13740v1,https://arxiv.org/pdf/2511.13740v1,arxiv,,"We study the nonlinear oscillator z'' + omega^2 z + g(t) z^2 = 0 with a time-dependent coefficient g(t). We show that this equation admits an exact quadratic invariant I(z,p,t) provided that g(t) = alpha2(t)^(-5/2) and that alpha2(t) satisfies a nonlinear third-order differential equation. The resul" | |
| 213,,Enhancing Visual Re-Ranking Through Denoising Nearest Neighbor Graph via Continuous CRF,Jaeyoon Kim; Yoonki Cho; Taeyong Kim; Sung-eui Yoon,2024,International Conference on Information Photonics,,,,,0,0.000,0.171,10.1109/icip55913.2025.11084658,https://www.semanticscholar.org/paper/851a21693baa922bfc0224c8d35219c5f9c6db48,,semantic_scholar,,"Nearest neighbor (NN) graph based visual re-ranking has emerged as a powerful approach for improving retrieval accuracy, offering the advantages of effectively exploring high-dimensional manifolds without requiring additional fine-tuning. However, the effectiveness of NN graph-based re-ranking is fu" | |
| 214,,Imagining Indian Nation-State: Rereading Qurratulain Hyder’s Select Novels in Contemporary Scenario,SK Sagir Ali,2023,Southeast Asian Review of English,,,,,0,0.000,0.150,10.22452/sare.vol60no2.6,https://www.semanticscholar.org/paper/81ec190912c91d35ad9f8da67515593bbb28d1fd,https://sare.um.edu.my/index.php/SARE/article/download/46065/16548,semantic_scholar,,"Given the contemporary hyper-nationalist ambiance in the Indian subcontinent, the reading of Qurratulain Hyder is significant, especially from the decolonial nationalist perspective of her selected translated Urdu novels. The paper examines the events and metaphors in both novels through a decolonia" | |
| 215,,Classifying bi-invariant 2-forms on infinite-dimensional Lie groups,David Michael Roberts,2023,,,,,,0,0.000,0.145,,https://www.semanticscholar.org/paper/e2e08eb06291f1b7dd89f9592079745ca0170bda,,semantic_scholar,,"A bi-invariant differential 2-form on a Lie group G is a highly constrained object, being determined by purely linear data: an Ad-invariant alternating bilinear form on the Lie algebra of G. On a compact connected Lie group these have an known classification, in terms of de Rham cohomology, which is" | |
| 216,,Higher category theory and n-groups as gauge symmetries for quantum gravity,B. Nikolić; D. Obrić; T. Radenković; Igor Salom; M. Vojinović,2023,Journal of Physics: Conference Series,,,,,0,0.000,0.144,10.1088/1742-6596/2667/1/012019,https://www.semanticscholar.org/paper/43d5b6da123511d92659e4c0521b73593c8edbc2,https://iopscience.iop.org/article/10.1088/1742-6596/2667/1/012019/pdf,semantic_scholar,,"Higher category theory can be employed to generalize the notion of a gauge group to the notion of a gauge n-group. This novel algebraic structure is designed to generalize notions of connection, parallel transport and holonomy from curves to manifolds of dimension higher than one. Thus it generalize" | |
| 217,,An Open Unified Addressing System for 6G Communication Networks,Guanwen Li; D. Lou; A. Galis; Jinze Yang; Chuang Wang,2022,2022 IEEE Future Networks World Forum (FNWF),,,,,0,0.000,0.140,10.1109/FNWF55208.2022.00034,https://www.semanticscholar.org/paper/e052320b7d61e70e69f249f3052527051709a1ae,https://discovery.ucl.ac.uk/10166968/1/OUA_FNWF_WS7.pdf,semantic_scholar,,"With the rapid and continuous development of the Internet, it is foreseeable that current addressing schemes and fixed-length IP addresses would create further bottlenecks and limitations in realizing future 6G networking requirements, such as massive connections, resource-constrained communication," | |
| 218,,Quantifying the Structure of Disordered Materials,T. Hardin; M. Chandross; Rahul Meena; Spencer Fajardo; Dimitris G. Giovanis,2022,,,,,,0,0.000,0.129,,https://www.semanticscholar.org/paper/10cb93831ff385c2d101ee4ad4390f58fe1f551c,,semantic_scholar,,"Durable interest in developing a framework for the detailed structure of glassy materials has produced numerous structural descriptors that trade off between general applicability and interpretability. However, none approach the combination of simplicity and wide-ranging predictive power of the latt" | |
| 219,,Data Decomposition for Constrained Visual Learning,Calvin Murdock,2021,,,,,,0,0.000,0.122,10.1184/r1/13557188.v1,https://www.semanticscholar.org/paper/dacdd39afbc3c27ca122634b19cacae1f72e7128,,semantic_scholar,, | |
| 220,,"GNPHE / 03-04 hep-th / 0303198 M-theory on G 2 manifolds and the method of ( p , q ) brane webs",A. Belhaj,2022,,,,,,0,0.000,0.120,,https://www.semanticscholar.org/paper/dde5ad445fcd6894ccddaa7c3ebe9f02420939f9,,semantic_scholar,, | |
| 221,,Optimal Mass Transport Meets Thermodynamics: On Power and Efficiency of Finite-Time Thermodynamic Engines,Huidong Chen,2022,,,,,,0,0.000,0.120,,https://www.semanticscholar.org/paper/a3ebed9b1e75a528f8e943275bdb99ffe515ab2c,,semantic_scholar,, | |
| 222,,"Countably Tangential, Continuous, Finitely Ultra-p-Adic Polytopes over Smoothly Left-Irreducible Fields",A. Repin,2021,,,,,,0,0.000,0.108,10.17762/MSEA.V70I2.13,https://www.semanticscholar.org/paper/5fd5346fc3f80ea084e60f4e8fdaa5f3c8226882,https://doi.org/10.17762/msea.v70i2.13,semantic_scholar,,"Vol. 70 No. 2 (2021), pages: 54-64 http://philstat.org.ph 54 Recently, there has been much interest in the computation of tangential systems. The groundbreaking work of F. Shastri on algebras was a major advance. Now this could shed important light on a conjecture of Russell. This reduces the result" | |
| 223,,Study of Hypersurface of semi-almost Hermitian manifold equipped with quarter-symmetric non-metric connection,Pankaj Pandey; B. B. Chaturvedi; Ejaz Sabir Lone,2020,Journal of Physics: Conference Series,,,,,0,0.000,0.107,10.1088/1742-6596/1531/1/012051,https://www.semanticscholar.org/paper/8e1abe414f9ecffe4077b17ad44f01f5eb62257a,https://doi.org/10.1088/1742-6596/1531/1/012051,semantic_scholar,,"In this paper, an induced connection on a Hyper surface ofa semi-almost Hermitian manifold equipped with a quarter-symmetric non-metric connection is studied and proved that induced connection is also a quarter-symmetricnon-metric connection.Further, we have obtained We ingarten equation, equation o" | |
| 224,,Ju l 2 01 0 SPIN STRUCTURES AND SUPERSTRINGS,J. Distler; D. Freed; G. Moore,2021,,,,,,0,0.000,0.100,,https://www.semanticscholar.org/paper/37722386089404be1451f8bb81f0a39404ffbb6e,,semantic_scholar,, | |
| 225,,ATCN: Agile Temporal Convolutional Networks for Processing of Time Series on Edge,Mohammadreza Baharani; Steven Furgurson; B. Parkhideh; Hamed Tabkhi,2020,arXiv.org,,,,,0,0.000,0.080,,https://www.semanticscholar.org/paper/f5767438cc43a73ce35b55227058ca4f37d97ce5,,semantic_scholar,, | |
| 226,,Ode to an ODE,Krzysztof Choromanski; Jared Quincy Davis; Valerii Likhosherstov; Xingyou Song; Jean-Jacques E. Slotine,2020,Neural Information Processing Systems,,,,,0,0.000,0.080,,https://www.semanticscholar.org/paper/e45547e6c081920e4749d825d72de077024c083f,,semantic_scholar,, | |
| 227,,On Transfer Learning Techniques for Machine Learning,Debasmit Das,2020,,,,,,0,0.000,0.080,10.25394/PGS.12221597.V1,https://www.semanticscholar.org/paper/4e665cdc829064719b778137b62d67ee88aa4f57,,semantic_scholar,, | |