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Tractable Computation of Expected Kernels by Circuits

Feb 21, 2021
Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck


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Probabilistic Generating Circuits

Feb 19, 2021
Honghua Zhang, Brendan Juba, Guy Van den Broeck


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A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries

Feb 11, 2021
Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck


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Group Fairness by Probabilistic Modeling with Latent Fair Decisions

Sep 18, 2020
YooJung Choi, Meihua Dang, Guy Van den Broeck


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On the Tractability of SHAP Explanations

Sep 18, 2020
Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu


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Strudel: Learning Structured-Decomposable Probabilistic Circuits

Jul 18, 2020
Meihua Dang, Antonio Vergari, Guy Van den Broeck

* 13 pages, 9 figures, to be published on PGM2020 (The 10th International Conference on Probabilistic Graphical Models) 

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Handling Missing Data in Decision Trees: A Probabilistic Approach

Jun 29, 2020
Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck


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On the Relationship Between Probabilistic Circuits and Determinantal Point Processes

Jun 26, 2020
Honghua Zhang, Steven Holtzen, Guy Van den Broeck


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Counterexample-Guided Learning of Monotonic Neural Networks

Jun 16, 2020
Aishwarya Sivaraman, Golnoosh Farnadi, Todd Millstein, Guy Van den Broeck


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On Effective Parallelization of Monte Carlo Tree Search

Jun 15, 2020
Anji Liu, Yitao Liang, Ji Liu, Guy Van den Broeck, Jianshu Chen


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Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Apr 13, 2020
Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani


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Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing

Feb 28, 2020
Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck


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Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration

Feb 27, 2020
Anji Liu, Yitao Liang, Guy Van den Broeck

* In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems, IFAAMAS 2020 

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Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings

Feb 24, 2020
Tal Friedman, Guy Van den Broeck


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LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning

Dec 06, 2019
Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto


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On Tractable Computation of Expected Predictions

Oct 31, 2019
Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck


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Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing

Sep 30, 2019
Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck


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Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing

Sep 20, 2019
Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck


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Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns

Jun 10, 2019
YooJung Choi, Golnoosh Farnadi, Behrouz Babaki, Guy Van den Broeck


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Smoothing Structured Decomposable Circuits

Jun 01, 2019
Andy Shih, Guy Van den Broeck, Paul Beame, Antoine Amarilli


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On Constrained Open-World Probabilistic Databases

Apr 02, 2019
Tal Friedman, Guy Van den Broeck


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Efficient Search-Based Weighted Model Integration

Mar 21, 2019
Zhe Zeng, Guy Van den Broeck


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Generating and Sampling Orbits for Lifted Probabilistic Inference

Mar 14, 2019
Steven Holtzen, Todd Millstein, Guy Van den Broeck


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What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features

Mar 05, 2019
Pasha Khosravi, Yitao Liang, YooJung Choi, Guy Van den Broeck


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Learning Logistic Circuits

Feb 27, 2019
Yitao Liang, Guy Van den Broeck

* @proceedings{liang2019logistic, title = {Proceedings of the Thirty-Third {AAAI} Conference on Artificial Intelligence (AAAI-19)}, publisher = {{AAAI} Press}, year = {2019} } 
* Published in the Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI19) 

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A Semantic Loss Function for Deep Learning with Symbolic Knowledge

Jun 08, 2018
Jingyi Xu, Zilu Zhang, Tal Friedman, Yitao Liang, Guy Van den Broeck

* This version appears in the Proceedings of the 35th International Conference on Machine Learning (ICML 2018) 

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Approximate Knowledge Compilation by Online Collapsed Importance Sampling

May 31, 2018
Tal Friedman, Guy Van den Broeck

* paper + supplementary material 

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On Robust Trimming of Bayesian Network Classifiers

May 29, 2018
YooJung Choi, Guy Van den Broeck


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