Guy Van den Broeck

UCLA - Computer Science Department
Engineering VI Room 368A
404 Westwood Plaza
Los Angeles, CA 90095-1596

Pronounce my name
guyvdb@cs.ucla.edu
guy@sigmoid.social
@guyvdb

I am a Professor of Computer Science and Samueli Fellow at UCLA, where I direct the Statistical and Relational Artificial Intelligence (StarAI) lab. My research interests are in Machine Learning (Tractable Deep Generative Models, Statistical Relational Learning, Probabilistic Programming), Knowledge Representation and Reasoning (Probabilistic Inference, Probabilistic Databases), and Artificial Intelligence in general.

Recent Publications

2025
[229]	Ryan Tjoa, Poorva Garg, Harrison Goldstein, Todd Millstein, Benjamin C. Pierce and Guy Van den Broeck. Tuning Random Generators: Property-Based Testing as Probabilistic Programming, In , ACM, 2025.
[228]	Poorva Garg, Benjie Wang, Oliver Broadrick, Guy Van den Broeck and Todd Millstein. Bitblasting for Constrained Decorrelation in Tractable Image Modeling, In Proceedings of the UAI Workshop on Tractable Probabilistic Modeling (TPM), 2025.
[227]	Honghua Zhang, Meihua Dang, Benjie Wang, Stefano Ermon, Nanyun Peng and Guy Van den Broeck. Scaling Probabilistic Circuits via Monarch Matrices, In Proceedings of the 42th International Conference on Machine Learning (ICML), 2025.
[226]	Gwen Yidou-Weng, Benjie Wang and Guy Van den Broeck. TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation, In Proceedings of the 42th International Conference on Machine Learning (ICML), 2025.
[225]	Xuejie Liu, Anji Liu, Yitao Liang and Guy Van den Broeck. Plug-and-Play Context Feature Reuse for Efficient Masked Generation, In Arxiv, 2025.
[224]	Anji Liu and Guy Van den Broeck. Rethinking Probabilistic Circuit Parameter Learning, In Arxiv, 2025.
[223]	Anji Liu, Xuejie Liu, Dayuan Zhao, Mathias Niepert, Yitao Liang and Guy Van den Broeck. Tractable Transformers for Flexible Conditional Generation, In Proceedings of the 42th International Conference on Machine Learning (ICML), 2025.
[222]	Renato Geh, Zilei Shao and Guy Van den Broeck. Adversarial Tokenization, In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 2025.
[221]	Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck and Markus Bläser. The Limits of Tractable Marginalization, In Proceedings of the 42th International Conference on Machine Learning (ICML), 2025.
[220]	Vinh Tong, Yun Ye, Dung Trung Hoang, Anji Liu, Guy Van den Broeck and Mathias Niepert. Symmetry-Preserving Diffusion Models via Target Symmetrization, In ICLR'25 workshop on DeLTA - Deep Generative Model in Machine Learning, 2025.