Peter Hayes

According to our database, Peter Hayes authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

Mingtian Zhang, Shawn Lan, Peter Hayes, David Barber

CoRR, 2024

Active Preference Learning for Large Language Models.

William Muldrew, Peter Hayes, Mingtian Zhang, David Barber

CoRR, 2024

2023

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

2022

Towards Healing the Blindness of Score Matching.

Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol

CoRR, 2022

Integrated Weak Learning.

Peter Hayes, Mingtian Zhang, Raza Habib, Jordan Burgess, Emine Yilmaz, David Barber

CoRR, 2022

Generalization Gap in Amortized Inference.

Mingtian Zhang, Peter Hayes, David Barber

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Sample Efficient Model Evaluation.

Emine Yilmaz, Peter Hayes, Raza Habib, Jordan Burgess, David Barber

CoRR, 2021

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

2020

Spread Divergence.

Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber

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