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Revisiting Structured Variational Autoencoders
Here, we revisit SVAEs using modern machine learning tools and demonstrate their advantages over more general alternatives in terms of both accuracy and efficiency.
BlockPuzzle - A Challenge in Physical Reasoning and Generalization for Robot Learning
In this work we propose a novel task framework under which a variety of physical reasoning puzzles can be constructed using very simple rules.
An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification
Existing subtomogram alignment based methods are prone to the missing wedge effects and low signal-to-noise ratio (SNR).
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study
To address this issue, we propose to measure the dependency instead of MI between layers in DNNs.
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