Stein variational message passing for continuous graphical models D Wang, Z Zeng, Q Liu
International Conference on Machine Learning, 5206-5214, 2018
60 2018 Efficient Search-Based Weighted Model Integration Z Zeng, GV Broeck
The Conference on Uncertainty in Artificial Intelligence (UAI), 2019
28 2019 SIMPLE: A Gradient Estimator for k-Subset Sampling Z Zeng, M Niepert, G Van den Broeck
The Eleventh International Conference on Learning Representations, 2023
23 * 2023 Probabilistically Rewired Message-Passing Neural Networks C Qian, A Manolache, K Ahmed, Z Zeng, G Van den Broeck, M Niepert, ...
The Twelfth International Conference on Learning Representations, 2024
17 2024 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
17 2020 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
14 2020 Collapsed inference for bayesian deep learning Z Zeng, G Van den Broeck
Advances in Neural Information Processing Systems 36, 78394-78411, 2023
10 2023 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
9 2021 A Unified Approach to Count-Based Weakly Supervised Learning V Shukla, Z Zeng, K Ahmed, G Van den Broeck
Advances in Neural Information Processing Systems 36, 38709-38722, 2023
7 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
5 2021 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
3 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
2 2020 Neurosymbolic Learning and Reasoning for Trustworthy AI Z Zeng
University of California, Los Angeles, 2024
1 2024 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 Deep Generative Models with Hard Linear Equality Constraints R Li, DR Sahu, GV Broeck, Z Zeng
arXiv preprint arXiv:2502.05416, 2025
2025 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 Gradient Estimation For Exactly- R Li, DR Sahu, G Van den Broeck, Z Zeng
NeurIPS 2023 AI for Science Workshop, 0
Guy Van den BroeckProfessor and Samueli Fellow, UCLAEmail verificata su cs.ucla.edu