Mingtian Zhang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Lossless Compression

Mild Assumptions

Top Venues

Nat. Mac. Intell.

Publications

Mingtian Zhang, Shawn Lan, Peter Hayes, David Barber
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning. CoRR (2024)
Zijing Ou, Mingtian Zhang, Andi Zhang, Tim Z. Xiao, Yingzhen Li, David Barber
Diffusion Model With Optimal Covariance Matching. CoRR (2024)
William Muldrew, Peter Hayes, Mingtian Zhang, David Barber
Active Preference Learning for Large Language Models. CoRR (2024)
Wenlin Chen, Mingtian Zhang, Brooks Paige, José Miguel Hernández-Lobato, David Barber
Diffusive Gibbs Sampling. CoRR (2024)
Liyuan Wang, Xingxing Zhang, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, Yi Zhong
Incorporating neuro-inspired adaptability for continual learning in artificial intelligence. Nat. Mac. Intell. 5 (12) (2023)
Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber
Moment Matching Denoising Gibbs Sampling. CoRR (2023)
Liyuan Wang, Xingxing Zhang, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, Yi Zhong
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence. CoRR (2023)
Mingtian Zhang, Yitong Sun, Chen Zhang, Steven McDonagh
Spread Flows for Manifold Modelling. AISTATS (2023)
Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber
Moment Matching Denoising Gibbs Sampling. NeurIPS (2023)
Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol
Towards Healing the Blindness of Score Matching. CoRR (2022)
Mingtian Zhang, Tim Z. Xiao, Brooks Paige, David Barber
Improving VAE-based Representation Learning. CoRR (2022)
Mingtian Zhang, Andi Zhang, Tim Z. Xiao, Yitong Sun, Steven McDonagh
Out-of-Distribution Detection with Class Ratio Estimation. CoRR (2022)
Mingtian Zhang, Peter Hayes, David Barber
Generalization Gap in Amortized Inference. NeurIPS (2022)
Mingtian Zhang, Peter Hayes, David Barber
Generalization Gap in Amortized Inference. CoRR (2022)
Mingtian Zhang, James Townsend, Ning Kang, David Barber
Parallel Neural Local Lossless Compression. CoRR (2022)
Peter Hayes, Mingtian Zhang, Raza Habib, Jordan Burgess, Emine Yilmaz, David Barber
Integrated Weak Learning. CoRR (2022)
Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong
AFEC: Active Forgetting of Negative Transfer in Continual Learning. CoRR (2021)
Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong
AFEC: Active Forgetting of Negative Transfer in Continual Learning. NeurIPS (2021)
Mingtian Zhang, Andi Zhang, Steven McDonagh
On the Out-of-distribution Generalization of Probabilistic Image Modelling. NeurIPS (2021)
Mingtian Zhang, Yitong Sun, Steven McDonagh, Chen Zhang
Flow Based Models For Manifold Data. CoRR (2021)
Mingtian Zhang, Andi Zhang, Steven McDonagh
On the Out-of-distribution Generalization of Probabilistic Image Modelling. CoRR (2021)
Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber
Spread Divergence. ICML (2020)
Mohammed Amin Abdullah, Hang Ren, Haitham Bou-Ammar, Vladimir Milenkovic, Rui Luo, Mingtian Zhang, Jun Wang
Wasserstein Robust Reinforcement Learning. CoRR (2019)
Mingtian Zhang, Thomas Bird, Raza Habib, Tianlin Xu, David Barber
Variational f-divergence Minimization. CoRR (2019)
David Barber, Mingtian Zhang, Raza Habib, Thomas Bird
Spread Divergences. CoRR (2018)