Publications | Mingtian Zhang

Selected Publications

Moment Matching Denoising Gibbs Sampling
NeurIPS 2023
Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber
Spread Flows for Manifold Modelling
AISTATS 2023
Mingtian Zhang, Yitong Sun, Steven McDonagh, Chen Zhang
Generalization Gap in Amortized Inference
NeurIPS 2022
Mingtian Zhang, Peter Hayes, David Barber
Towards Healing the Blindness of Score Matching
Score-Based Methods Workshop, NeurIPS 2022
Mingtian Zhang, Oscar Keys, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol
Out-of-Distribution Detection with Class Ratio Estimation
Machine Learning Safety Workshop, NeurIPS 2022
Mingtian Zhang, Andi Zhang, Tim Xiao, Yitong Sun, Steven McDonagh
Integrated Weak Learning
ArXiv preprint
Peter Hayes, Mingtian Zhang, Raza Habib, Jordan Burgess, Emine Yilmaz, David Barber
Improving VAE-based Representation Learning
ArXiv preprint
Mingtian Zhang, Tim Xiao, Brooks Paige, David Barber
Parallel Neural Local Lossless Compression
ArXiv preprint
Mingtian Zhang, James Townsend, Ning Kang, David Barber
On the Out-of-Distribution Generalization of Probabilistic Image Modelling
NeurIPS 2021
Mingtian Zhang, Andi Zhang, Steven McDonagh
Active Forgetting of Negative Transfer in Continual Learning
NeurIPS 2021
Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Kaisheng Ma, Chenglong Bao, Jun Zhu, Yi Zhong
Solipsistic Reinforcement Learning
Self-Supervision for Reinforcement Learning Workshop, ICLR 2021
Mingtian Zhang, Peter Hayes, Tim Xiao, Andi Zhang, David Barber
Spread Divergence
ICML 2020
Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber
Variational f-Divergence Minimization
Information Theory and Machine Learning Workshop, NeurIPS 2019
Mingtian Zhang, Thomas Bird, Raza Habib, Tianlin Xu, David Barber