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Learning to Fly via Deep Model-Based Reinforcement Learning
Learning to control robots without requiring models has been a long-term...
03/19/2020 ∙ by Philip Becker-Ehmck, et al. ∙
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Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations
Learning a model of dynamics from high-dimensional images can be a core ...
11/02/2019 ∙ by Neha Das, et al. ∙
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Switching Linear Dynamics for Variational Bayes Filtering
System identification of complex and nonlinear systems is a central prob...
05/29/2019 ∙ by Philip Becker-Ehmck, et al. ∙
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Unsupervised Real-Time Control through Variational Empowerment
We introduce a methodology for efficiently computing a lower bound to em...
10/13/2017 ∙ by Maximilian Karl, et al. ∙
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