Guy Van den Broeck

UCLA - Computer Science Department
4531E Boelter Hall
Los Angeles, CA 90095-1596
+1 (310) 206-6552

I am an Assistant Professor and Samueli Fellow at UCLA, in the Computer Science Department, where I direct the Statistical and Relational Artificial Intelligence (StarAI) lab. My research interests are in Machine Learning (Statistical Relational Learning, Tractable Learning), Knowledge Representation and Reasoning (Graphical Models, Lifted Probabilistic Inference, Knowledge Compilation), Applications of Probabilistic Reasoning and Learning (Probabilistic Programming, Probabilistic Databases), and Artificial Intelligence in general. I previously was a postdoctoral researcher at UCLA’s Automated Reasoning lab and KU Leuven’s Declarative Languages and Artificial Intelligence lab.

Recent Publications

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[74], , and . New Liftable Classes for First-Order Probabilistic Inference, In Advances in Neural Information Processing Systems 29 (NIPS), . [bibtex] [pdf]
[73], and . Algebraic Model Counting, In International Journal of Applied Logic, . [bibtex] [pdf] [doi]
[72], , and . Robust Channel Coding Strategies for Machine Learning Data, In Proceedings of the 54th Annual Allerton Conference on Communication, Control, and Computing, . [bibtex] [pdf]
[71], and . Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report, In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), Sister Conference Best Paper Track, . [bibtex] [pdf]
[70]. First-Order Model Counting in a Nutshell, In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), Early Career Spotlight Track, . [bibtex] [pdf]
[69], , , and . Tp-Compilation for Inference in Probabilistic Logic Programs, In International Journal of Approximate Reasoning, . [bibtex] [pdf] [doi]
[68], and . Open-World Probabilistic Databases, In Proceedings of the 15th International Conference on Principles of Knowledge Representation and Reasoning (KR), . [bibtex] [pdf]
KR best student paper award
[67], , and . Exploiting Local and Repeated Structure in Dynamic Bayesian Networks, In Artificial Intelligence, volume 232, . [bibtex] [pdf] [doi]
[66], and . Component Caching in Hybrid Domains with Piecewise Polynomial Densities, In Proceedings of the 30th Conference on Artificial Intelligence (AAAI), . [bibtex] [pdf]
[65], and . A Relaxed Tseitin Transformation for Weighted Model Counting, . International Workshop on Statistical Relational AI [bibtex] [pdf]