32 citations · 69 across the 7 of their papers we have counts for
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cs.LG2019★ 1 cited
Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations
Neha Das, Maximilian Karl, Philip Becker-Ehmck +1
Learning a model of dynamics from high-dimensional images can be a core ingredient for success in many applications across different domains, especially in sequential decision maki…
stat.ML2019★ 32 cited
Switching Linear Dynamics for Variational Bayes Filtering
Philip Becker-Ehmck, Jan Peters, Patrick van der Smagt
System identification of complex and nonlinear systems is a central problem for model predictive control and model-based reinforcement learning. Despite their complexity, such syst…