Spread Divergence. - Mingtian Zhang; Peter Hayes; Thomas Bird; Raza Habib; David Barber (ICML, 2020)

Estimating the Uncertainty of Neural Network Forecasts for Influenza Prevalence Using Web Search Activity. - Michael Morris; Peter Hayes; Ingemar J. Cox; Vasileios Lampos (CoRR, 2021)

Sample Efficient Model Evaluation. - Emine Yilmaz; Peter Hayes; Raza Habib; Jordan Burgess; David Barber (CoRR, 2021)

Generalization Gap in Amortized Inference. - Mingtian Zhang; Peter Hayes; David Barber (NeurIPS, 2022)

Integrated Weak Learning. - Peter Hayes; Mingtian Zhang; Raza Habib; Jordan Burgess; Emine Yilmaz; David Barber (CoRR, 2022)

Towards Healing the Blindness of Score Matching. - Mingtian Zhang; Oscar Key; Peter Hayes; David Barber; Brooks Paige; François-Xavier Briol (CoRR, 2022)

Neural network models for influenza forecasting with associated uncertainty using Web search activity trends. - Michael Morris; Peter Hayes; Ingemar J. Cox; Vasileios Lampos (PLoS Comput. Biol., 2023)

Active Preference Learning for Large Language Models. - William Muldrew; Peter Hayes; Mingtian Zhang; David Barber (ICML, 2024)

Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning. - Mingtian Zhang; Shawn Lan; Peter Hayes; David Barber (CoRR, 2024)