9 citations · 29 across the 14 of their papers we have counts for
5 papers · 1 filter
Entropic Matching for Expectation Propagation of Markov Jump Processes
Yannick Eich, Bastian Alt, Heinz Koeppl
We propose a novel, tractable latent state inference scheme for Markov jump processes, for which exact inference is often intractable. Our approach is based on an entropic matching…
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems
Lukas Köhs, Bastian Alt, Heinz Koeppl
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 stu…
Variational Inference for Continuous-Time Switching Dynamical Systems
Lukas Köhs, Bastian Alt, Heinz Koeppl
Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since…
POMDPs in Continuous Time and Discrete Spaces
Bastian Alt, Matthias Schultheis, Heinz Koeppl
Many processes, such as discrete event systems in engineering or population dynamics in biology, evolve in discrete space and continuous time. We consider the problem of optimal de…
Correlation Priors for Reinforcement Learning
Bastian Alt, Adrian Šošić, Heinz Koeppl
Many decision-making problems naturally exhibit pronounced structures inherited from the characteristics of the underlying environment. In a Markov decision process model, for exam…