Bert de Vries
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The paper introduces a framework for composing deep probabilistic models using five specific factor-graph primitives that guarantee closed-form variational inference, thereby preserving tractability in complex architectures.
This paper provides a detailed message-passing scheme for EFE-based planning and clarifies the corrections needed for cross-entropy planning and full EFE-based planning.
This paper argues that the choice of divergence in statistical inference can be justified by requiring invariance to problem reformulations, leading to the selection of the Kullback-Leibler divergence.
Papers
Reformulation Invariance and the Axiomatic Foundations of Inference
This paper argues that the choice of divergence in statistical inference can be justified by requiring invariance to problem reformulations, leading to the selection of the Kullback-Leibler divergence…