Publications

EventFlow: Forecasting Temporal Point Processes with Flow Matching

Gavin Kerrigan, Kai Nelson, Padhraic Smyth

International Conference on AI and Statistics (AISTATS), 2026.
[Oral, top 0.5% of submissions]

• arXiv

A Geometric Approach to Optimal Experimental Design

Gavin Kerrigan, Christian A. Naesseth, Tom Rainforth

International Conference on AI and Statistics (AISTATS), 2026.

• arXiv
• Code

Scaling Bayesian Experimental Design to High-Dimensions with Information-Guided Diffusion

Adhi Saravanan, Rik Knowles, Gavin Kerrigan, Tom Rainforth

International Conference on Learning Representations (ICLR), 2026.

• Publication

Guided Diffusion Sampling on Function Spaces with Applications to PDEs

Jiachen Yao, Abbas Mammadov, Julius Berner, Gavin Kerrigan, Jong Chul Ye, Kamyar Azizzadenesheli, Anima Anandkumar

Neural Information Processing Systems (NeurIPS), 2025.

• arXiv
• Code

A Generative Diffusion Model for Probabilistic Ensembles of Precipitation Maps Conditioned on Multisensor Satellite Observations

Clement Guilloteau, Gavin Kerrigan, Kai Nelson, Giosue Migliorini, Padhraic Smyth, Runze Li, Efi Foufoula-Georgiou

IEEE Transactions on Geoscience and Remote Sensing, 2025.

• Publication
• arXiv

Dynamic Conditional Optimal Transport through Simulation-Free Flows

Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth

Neural Information Processing Systems (NeurIPS), 2024.

• arXiv
• Code

Precipitation Downscaling with Spatiotemporal Video Diffusion

Prakhar Srivastava, Ruihan Yang, Gavin Kerrigan, Gideon Dresdner, Jeremy McGibbon, Christopher Bretherton, Stephan Mandt

Neural Information Processing Systems (NeurIPS), 2024.

• arXiv

Functional Flow Matching

Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth

International Conference on AI and Statistics (AISTATS), 2024.
[Oral, Outstanding Student Paper Highlight, 7/2181 submissions]

• Publication
• arXiv
• Code

Diffusion Generative Models in Infinite Dimensions

Gavin Kerrigan, Justin Ley, Padhraic Smyth

International Conference on AI and Statistics (AISTATS), 2023.

• Publication
• arXiv
• Code

Bayesian Modeling of Human-AI Complementarity

Mark Steyvers, Heliodoro Tejeda, Gavin Kerrigan, Padhraic Smyth

Proceedings of the National Academy of Sciences (PNAS), 2022.

• Publication
• Code
• Blog
• Press

Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration

Gavin Kerrigan, Padhraic Smyth, Mark Steyvers

Neural Information Processing Systems (NeurIPS), 2021.

• Publication
• arXiv
• Code

Differentially Private Language Models Benefit from Public Pre-Training

Gavin Kerrigan*, Dylan Slack*, Jens Tuyls*

PrivateNLP : EMNLP Workshop on Privacy and Natural Language Processing, 2020.

• Publication
• arXiv
• Code