Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning to Correspond Dynamical Systems   Many dynamical systems exhibit similar structure, as often captured by
hand-designed simplified models that can be used for analysis and control. We
develop a method for learning to correspond pairs of dynamical systems via a
learned latent dynamical system. Given trajectory data from two dynamical
systems, we learn a shared latent state space and a shared latent dynamics
model, along with an encoder-decoder pair for each of the original systems.
With the learned correspondences in place, we can use a simulation of one
system to produce an imagined motion of its counterpart. We can also simulate
in the learned latent dynamics and synthesize the motions of both corresponding
systems, as a form of bisimulation. We demonstrate the approach using pairs of
controlled bipedal walkers, as well as by pairing a walker with a controlled
pendulum.

13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
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The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
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The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas