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Zhe Zeng
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Cited by
Cited by
Year
Stein variational message passing for continuous graphical models
D Wang, Z Zeng, Q Liu
International Conference on Machine Learning, 5206-5214, 2018
592018
Efficient Search-Based Weighted Model Integration
Z Zeng, GV Broeck
The Conference on Uncertainty in Artificial Intelligence (UAI), 2019
242019
SIMPLE: A Gradient Estimator for k-Subset Sampling
Z Zeng, M Niepert, G Van den Broeck
The Eleventh International Conference on Learning Representations, 2023
17*2023
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
142020
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
112020
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
92021
Collapsed inference for bayesian deep learning
Z Zeng, G Van den Broeck
Advances in Neural Information Processing Systems 36, 2024
52024
Probabilistically rewired message-passing neural networks
C Qian, A Manolache, K Ahmed, Z Zeng, GV Broeck, M Niepert, C Morris
arXiv preprint arXiv:2310.02156, 2023
52023
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
32021
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, 2024
22024
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
22019
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
12023
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
12020
Neurosymbolic Learning and Reasoning for Trustworthy AI
Z Zeng
UCLA, 2024
2024
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- Constraints
R Li, DR Sahu, G Van den Broeck, Z Zeng
NeurIPS 2023 AI for Science Workshop, 0
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