Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with
  State-Dependent Event Rates   Numerical Generalized Randomized Hamiltonian Monte Carlo is introduced, as a
robust, easy to use and computationally fast alternative to conventional Markov
chain Monte Carlo methods for continuous target distributions. A wide class of
piecewise deterministic Markov processes generalizing Randomized HMC (Bou-Rabee
and Sanz-Serna, 2017) by allowing for state-dependent event rates is defined.
Under very mild restrictions, such processes will have the desired target
distribution as an invariant distribution. Secondly, the numerical
implementation of such processes, based on adaptive numerical integration of
second order ordinary differential equations (ODEs) is considered. The
numerical implementation yields an approximate, yet highly robust algorithm
that, unlike conventional Hamiltonian Monte Carlo, enables the exploitation of
the complete Hamiltonian trajectories (hence the title). The proposed algorithm
may yield large speedups and improvements in stability relative to relevant
benchmarks, while incurring numerical biases that are negligible relative to
the overall Monte Carlo errors. Granted access to a high-quality ODE code, the
proposed methodology is both easy to implement and use, even for highly
challenging and high-dimensional target distributions.

36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph