Zhe Zeng

Affiliations:

University of Virginia, Department of Computer Science, Charlottesville, VA, USA
New York University, Computer Science Department, New York, NY, USA (2024 - 2025)
University of California, Los Angeles (UCLA), Computer Science Department, Los Angeles, CA, USA (PhD 2024)
Zhejiang University, School of Mathematical Sciences, Hangzhou, China (2014 - 2018)

According to our database¹, Zhe Zeng authored at least 15 papers between 2017 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2025

Deep Generative Models with Hard Linear Equality Constraints.

[BibT_eX]

[DOI]

CoRR, February, 2025

2024

Neurosymbolic Learning and Reasoning for Trustworthy AI

[BibT_eX]

[DOI]

Zhe Zeng

PhD thesis, 2024

Probabilistically Rewired Message-Passing Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Collapsed Inference for Bayesian Deep Learning.

[BibT_eX]

[DOI]

Zhe Zeng

Guy Van den Broeck

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Approach to Count-Based Weakly Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SIMPLE: A Gradient Estimator for k-Subset Sampling.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Unified Knowledge Distillation Framework for Deep Directed Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021

Tractable Computation of Expected Kernels by Circuits.

[BibT_eX]

[DOI]

CoRR, 2021

Tractable computation of expected kernels.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing.

[BibT_eX]

[DOI]

CoRR, 2019

Efficient Search-Based Weighted Model Integration.

[BibT_eX]

[DOI]

Zhe Zeng

Guy Van den Broeck

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Stein Variational Message Passing for Continuous Graphical Models.

[BibT_eX]

[DOI]

Dilin Wang

Zhe Zeng

Qiang Liu

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Structured Stein Variational Inference for Continuous Graphical Models.

[BibT_eX]

[DOI]

Dilin Wang

Zhe Zeng

Qiang Liu

CoRR, 2017

Zhe Zeng

Timeline

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