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
[222]	Gwen Yidou Weng, Benjie Wang and Guy Van den Broeck. TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation, In Arxiv, 2025.
[221]	Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck and Markus Bläser. The Limits of Tractable Marginalization, In Arxiv, 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.
[219]	Siyan Zhao, Daniel Israel, Guy Van den Broeck and Aditya Grover. Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models, In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025.
[218]	Honghua Zhang, Benjie Wang, Marcelo Arenas and Guy Van den Broeck. Restructuring Tractable Probabilistic Circuits, In Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025. Oral full presentation, acceptance rate 2%
[217]	Kareem Ahmed, Kai-Wei Chang and Guy Van den Broeck. Controllable Generation via Locally Constrained Resampling, In Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025.
[216]	Anji Liu, Oliver Broadrick, Mathias Niepert and Guy Van den Broeck. Discrete Copula Diffusion, In Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025.
[215]	Vinh Tong, Anji Liu, Trung-Dung Hoang, Guy Van den Broeck and Mathias Niepert. Learning to Discretize Denoising Diffusion ODEs, In Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025. Oral full presentation, acceptance rate 1.8%
[214]	Daniel Severo, Jingtong Su, Anji Liu, Jeff Johnson, Brian Karrer, Guy Van den Broeck, Matthew Muckley and Karen Ullrich. Enhancing and Evaluating Probabilistic Circuits for High-Resolution Lossless Image Compression, In Proceedings of the Data Compression Conference (DCC), 2025.
[213]	Benjie Wang and Guy Van den Broeck. On the Relationship between Monotone and Squared Probabilistic Circuits, In Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence, 2025.