| Stein variational message passing for continuous graphical models D Wang, Z Zeng, Q Liu International Conference on Machine Learning, 5206-5214, 2018 | 51 | 2018 |
| Efficient Search-Based Weighted Model Integration Z Zeng, GV Broeck The Conference on Uncertainty in Artificial Intelligence (UAI), 2019 | 21 | 2019 |
| Probabilistic inference with algebraic constraints: Theoretical limits and practical approximations Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck Advances in Neural Information Processing Systems 33, 11564-11575, 2020 | 10 | 2020 |
| Tractable computation of expected kernels W Li, Z Zeng, A Vergari, G Van den Broeck The Conference on Uncertainty in Artificial Intelligence (UAI), 1163-1173, 2021 | 8 | 2021 |
| Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Z Zeng, P Morettin, F Yan, A Vergari, GV Broeck Thirty-seventh International Conference on Machine Learning (ICML) 2020, 2020 | 8 | 2020 |
| SIMPLE: A Gradient Estimator for k-Subset Sampling Z Zeng, M Niepert, G Van den Broeck The Eleventh International Conference on Learning Representations, 2023 | 6* | 2023 |
| Is Parameter Learning via Weighted Model Integration Tractable? Z Zeng, P Morettin, F Yan, A Passerini, G Van den Broeck The 4th Workshop on Tractable Probabilistic Modeling (TPM) at Uncertainty in …, 2021 | 3 | 2021 |
| Collapsed Inference for Bayesian Deep Learning Z Zeng, GV Broeck arXiv preprint arXiv:2306.09686, 2023 | 1 | 2023 |
| Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing Z Zeng, F Yan, P Morettin, A Vergari, GV Broeck Workshop on Knowledge Representation & Reasoning Meets Machine Learning …, 2019 | 1 | 2019 |
| Probabilistic Task-Adaptive Graph Rewiring C Qian, A Manolache, K Ahmed, Z Zeng, G Van den Broeck, M Niepert, ... ICML 2023 Workshop on Differentiable Almost Everything: Differentiable …, 2023 | | 2023 |
| A Unified Approach to Count-Based Weakly-Supervised Learning V Shukla, Z Zeng, K Ahmed, G Van den Broeck ICML 2023 Workshop on Differentiable Almost Everything: Differentiable …, 2023 | | 2023 |
| A Unified Knowledge Distillation Framework for Deep Directed Graphical Models Y Chen, K Liang, Z Zeng, S Yao, H Shao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | | 2023 |
| Relax, compensate and then integrate Z Zeng, P Morettin, F Yan, A Vergari, G Van den Broeck Proceedings of the ECML-PKDD Workshop on Deep Continuous-Discrete Machine …, 2020 | | 2020 |
Guy Van den BroeckAssociate Professor and Samueli Fellow, UCLAVerified email at cs.ucla.edu
