Learning Graphical Models
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning. (Wikipedia)
0a97df4ce5b403ea87645010e9005130-Paper-Conference.pdf
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In this paper, we investigate integrating this inductive bias of sparse interactions into thelatent dynamics ofworld models trained from pixels.
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LearninginObservablePOMDPs, withoutComputationallyIntractableOracles
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Much ofreinforcement learning theory isbuiltontopoforacles that arecomputationally hard to implement.
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