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Poster
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Scaling Up Probabilistic Circuits by Latent Variable Distillation
Anji Liu · Honghua Zhang · Guy Van den Broeck
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Poster
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Mon 7:30
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Trading Information between Latents in Hierarchical Variational Autoencoders
Tim Xiao · Robert Bamler
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Oral
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Tue 6:40
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Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
Zihao Xu · Guang-Yuan Hao · Hao He · Hao Wang
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Poster
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Any-scale Balanced Samplers for Discrete Space
Haoran Sun · Bo Dai · Charles Sutton · Dale Schuurmans · Hanjun Dai
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Oral Session
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Tue 6:00
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Oral 4 Track 2: Probabilistic Methods
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Poster
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TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs
Siheng Xiong · Yuan Yang · Faramarz Fekri · James Kerce
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Oral Session
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Tue 6:00
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Oral 4 Track 5: Machine Learning for Sciences & Probabilistic Methods
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Poster
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Tue 7:30
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Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
Zihao Xu · Guang-Yuan Hao · Hao He · Hao Wang
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Poster
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Tue 7:30
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Causal Imitation Learning via Inverse Reinforcement Learning
Kangrui Ruan · Junzhe Zhang · Xuan Di · Elias Bareinboim
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Poster
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Mon 2:30
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A Neural Mean Embedding Approach for Back-door and Front-door Adjustment
Liyuan Xu · Arthur Gretton
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Poster
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Causal Estimation for Text Data with (Apparent) Overlap Violations
Lin Gui · Victor Veitch
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Poster
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Tue 2:30
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Bridge the Inference Gaps of Neural Processes via Expectation Maximization
Qi Wang · Marco Federici · Herke van Hoof
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