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Oral
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Tue 1:40
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The Complexity of Bayesian Network Learning: Revisiting the Superstructure
Robert Ganian · Viktoriia Korchemna
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Poster
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Tue 8:30
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Tractable Regularization of Probabilistic Circuits
Anji Liu · Guy Van den Broeck
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Poster
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Wed 0:30
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Coarse-to-fine Animal Pose and Shape Estimation
Chen Li · Gim Hee Lee
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Poster
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Thu 16:30
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Topographic VAEs learn Equivariant Capsules
T. Anderson Keller · Max Welling
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Poster
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Tue 16:30
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AC-GC: Lossy Activation Compression with Guaranteed Convergence
R David Evans · Tor Aamodt
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Poster
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Thu 8:30
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Scalable Inference of Sparsely-changing Gaussian Markov Random Fields
Salar Fattahi · Andres Gomez
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Poster
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Thu 0:30
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Causal Identification with Matrix Equations
Sanghack Lee · Elias Bareinboim
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Poster
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Tue 8:30
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BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
Chris Cundy · Aditya Grover · Stefano Ermon
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Poster
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Thu 16:30
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Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds
Shahrzad Haddadan · Yue Zhuang · Cyrus Cousins · Eli Upfal
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Poster
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Tue 8:30
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Fast Training of Neural Lumigraph Representations using Meta Learning
Alexander Bergman · Petr Kellnhofer · Gordon Wetzstein
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Poster
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Fri 8:30
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Efficient Online Estimation of Causal Effects by Deciding What to Observe
Shantanu Gupta · Zachary Lipton · David Childers
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Workshop
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Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
Sindy Löwe · David Madras · Richard Zemel · Max Welling
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