* denotes equal contribution

• Training Neural Samplers with Reverse Diffusive KL Divergence

  ArXiv Preprint

  Jiajun He*, Wenlin Chen*, Mingtian Zhang*, David Barber, José Miguel Hernández-Lobato

• Improving Probabilistic Diffusion Models With Optimal Covariance Matching

  ArXiv Preprint

  Zijing Ou*, Mingtian Zhang*, Andi Zhang, Tim Xiao, Yingzhen Li, David Barber

• Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling

  NeurIPS 2024

  Harry Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth

• Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning

  ArXiv Preprint

  Mingtian Zhang, Shawn Lan, Peter Hayes, David Barber

• Active Preference Learning for Large Language Models

  ICML 2024

  William Muldrew, Peter Hayes, Mingtian Zhang, David Barber

• Diffusive Gibbs Sampling

  ICML 2024

  Wenlin Chen*, Mingtian Zhang*, Brooks Paige, José Miguel Hernández-Lobato, David Barber

• 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