Efficient Search-Based Weighted Model Integration. - Zhe Zeng 001; Guy Van den Broeck (UAI, 2019)

Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing. - Zhe Zeng 001; Fanqi Yan; Paolo Morettin; Antonio Vergari; Guy Van den Broeck (CoRR, 2019)

Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing. - Zhe Zeng 001; Paolo Morettin; Fanqi Yan; Antonio Vergari; Guy Van den Broeck (ICML, 2020)

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations. - Zhe Zeng 001; Paolo Morettin; Fanqi Yan; Antonio Vergari; Guy Van den Broeck (NeurIPS, 2020)

Tractable computation of expected kernels. - Wenzhe Li; Zhe Zeng 001; Antonio Vergari; Guy Van den Broeck (UAI, 2021)

Tractable Computation of Expected Kernels by Circuits. - Wenzhe Li; Zhe Zeng 001; Antonio Vergari; Guy Van den Broeck (CoRR, 2021)

SIMPLE: A Gradient Estimator for k-Subset Sampling. - Kareem Ahmed; Zhe Zeng 001; Mathias Niepert; Guy Van den Broeck (ICLR, 2023)

A Unified Approach to Count-Based Weakly Supervised Learning. - Vinay Shukla; Zhe Zeng 001; Kareem Ahmed; Guy Van den Broeck (NeurIPS, 2023)

Collapsed Inference for Bayesian Deep Learning. - Zhe Zeng 001; Guy Van den Broeck (NeurIPS, 2023)

Probabilistically Rewired Message-Passing Neural Networks. - Chendi Qian; Andrei Manolache; Kareem Ahmed; Zhe Zeng 001; Guy Van den Broeck; Mathias Niepert; Christopher Morris 001 (ICLR, 2024)

Neurosymbolic Learning and Reasoning for Trustworthy AI - Zhe Zeng 001 (2024)

Deep Generative Models with Hard Linear Equality Constraints. - Ruoyan Li; Dipti Ranjan Sahu; Guy Van den Broeck; Zhe Zeng 001 (CoRR, 2025)