Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems. (arXiv:2205.08803v1 [cs.LG])

Switching dynamical systems are an expressive model class for the analysis of
time-series data. As in many fields within the natural and engineering
sciences, the systems under study typically evolve continuously in time, it is
natural to consider continuous-time model formulations consisting of switching
stochastic differential equations governed by an underlying Markov jump
process. Inference in these types of models is however notoriously difficult,
and tractable computational schemes are rare. In this work, we propose a novel
inference algorithm utilizing …

arxiv continuous markov systems time