Zeng, Zhe

15 publications

ICLR 2024 Probabilistically Rewired Message-Passing Neural Networks Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris

NeurIPS 2023 A Unified Approach to Count-Based Weakly Supervised Learning Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck

ICMLW 2023 A Unified Approach to Count-Based Weakly-Supervised Learning Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck

CVPR 2023 A Unified Knowledge Distillation Framework for Deep Directed Graphical Models Yizhuo Chen, Kaizhao Liang, Zhe Zeng, Shuochao Yao, Huajie Shao

NeurIPS 2023 Collapsed Inference for Bayesian Deep Learning Zhe Zeng, Guy Van den Broeck

ICMLW 2023 Collapsed Inference for Bayesian Deep Learning Zhe Zeng, Guy Van den Broeck

NeurIPSW 2023 Gradient Estimation for Exactly-$k$ Constraints Ruoyan Li, Dipti Ranjan Sahu, Guy Van den Broeck, Zhe Zeng

ICMLW 2023 Probabilistic Task-Adaptive Graph Rewiring Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris

ICMLW 2023 SIMPLE: A Gradient Estimator for $k$-Subset Sampling Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck

ICLR 2023 SIMPLE: A Gradient Estimator for K-Subset Sampling Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck

UAI 2021 Tractable Computation of Expected Kernels Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Broeck

NeurIPS 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck

ICML 2020 Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van Den Broeck

UAI 2019 Efficient Search-Based Weighted Model Integration Zhe Zeng, Guy Broeck

ICML 2018 Stein Variational Message Passing for Continuous Graphical Models Dilin Wang, Zhe Zeng, Qiang Liu