Tom Beucler

According to our database, Tom Beucler authored at least 27 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models.

Max Defez, Filippo Quarenghi, Mathieu Vrac, Stephan Mandt, Tom Beucler

CoRR, April, 2026

Emulating Non-Differentiable Metrics via Knowledge-Guided Learning: Introducing the Minkowski Image Loss.

Filippo Quarenghi, Ryan Cotsakis, Tom Beucler

CoRR, April, 2026

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning.

Savannah L. Ferretti, Jerry Lin, Sara Shamekh, Jane W. Baldwin, Michael S. Pritchard, Tom Beucler

CoRR, March, 2026

TCBench: A Benchmark for Tropical Cyclone Track and Intensity Forecasting at the Global Scale.

Milton S. Gomez, Marie McGraw, Saranya Ganesh S., Frederick Iat-Hin Tam, Ilia Azizi, Samuel Darmon, Monika Feldmann, Stella Bourdin, Louis Poulain-Auzéau, Suzana J. Camargo, Jonathan Lin, Dan Chavas, Chia-Ying Lee, Ritwik Gupta, Andrea M. Jenney, Tom Beucler

CoRR, January, 2026

2025

Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a $50,000 Kaggle Competition.

Jerry Lin, Zeyuan Hu, Tom Beucler, Katherine Frields, Hannah Christensen, Walter M. Hannah, Helge Heuer, Peter Ukkonnen, Laura A. Mansfield, Tian Zheng, Liran Peng, Ritwik Gupta, Pierre Gentine, Yusef Al-Naher, Mingjiang Duan, Kyo Hattori, Weiliang Ji, Chunhan Li, Kippei Matsuda, Naoki Murakami, Shlomo Ron, Marec Serlin, Hongjian Song, Yuma Tanabe, Daisuke Yamamoto, Jianyao Zhou, Mike Pritchard

CoRR, November, 2025

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting.

Saranya Ganesh S., Frederick Iat-Hin Tam, Milton S. Gomez, Marie McGraw, Mark DeMaria, Kate D. Musgrave, Jakob Runge, Tom Beucler

CoRR, October, 2025

Taking the Garbage Out of Data-Driven Prediction Across Climate Timescales.

Jason C. Furtado, Maria J. Molina, Marybeth C. Arcodia, Weston Anderson, Tom Beucler, John A. Callahan, Laura M. Ciasto, Vittorio A. Gensini, Michelle L'Heureux, Kathleen Pegion, Jhayron S. Perez-Carrasquilla, Maike Sonnewald, Ken Takahashi, Baoqiang Xiang, Brian G. Zimmerman

CoRR, August, 2025

Investigating the Robustness of Extreme Precipitation Super-Resolution Across Climates.

Louise Largeau, Erwan Koch, David Leutwyler, Grégoire Mariéthoz, Valérie Chavez-Demoulin, Tom Beucler

CoRR, July, 2025

Improving Predictions of Convective Storm Wind Gusts through Statistical Post-Processing of Neural Weather Models.

Antoine Leclerc, Erwan Koch, Monika Feldmann, Daniele Nerini, Tom Beucler

CoRR, April, 2025

ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation.

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard

J. Mach. Learn. Res., 2025

2024

Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications.

Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, Ryan Lagerquist

CoRR, 2024

Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models.

Monika Feldmann, Tom Beucler, Milton Gomez, Olivia Martius

CoRR, 2024

Identifying Three-Dimensional Radiative Patterns Associated with Early Tropical Cyclone Intensification.

Frederick Iat-Hin Tam, Tom Beucler, James H. Ruppert Jr.

CoRR, 2024

Lessons Learned: Reproducibility, Replicability, and When to Stop.

Milton S. Gomez, Tom Beucler

CoRR, 2024

2023

Next-Generation Earth System Models: Towards Reliable Hybrid Models for Weather and Climate Applications.

Tom Beucler, Erwan Koch, Sven Kotlarski, David Leutwyler, Adrien Michel, Jonathan Koh

CoRR, 2023

Systematic Sampling and Validation of Machine Learning-Parameterizations in Climate Models.

Jerry Lin, Sungduk Yu, Tom Beucler, Pierre Gentine, David Walling, Mike Pritchard

CoRR, 2023

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.

CoRR, 2023

Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery.

Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam, Milton S. Gomez, Jakob Runge, Andreas Gerhardus

CoRR, 2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.

Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Physics-constrained deep learning postprocessing of temperature and humidity.

Francesco Zanetta, Daniele Nerini, Tom Beucler, Mark A. Liniger

CoRR, 2022

2021

Deep Learning Based Cloud Cover Parameterization for ICON.

Arthur Grundner, Tom Beucler, Fernando Iglesias-Suarez, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring

CoRR, 2021

Climate-Invariant Machine Learning.

Tom Beucler, Michael S. Pritchard, Janni Yuval, Ankitesh Gupta, Liran Peng, Stephan Rasp, Fiaz Ahmed, Paul A. O'Gorman, J. David Neelin, Nicholas J. Lutsko, Pierre Gentine

CoRR, 2021

Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs.

Harshini Mangipudi, Griffin Mooers, Mike Pritchard, Tom Beucler, Stephan Mandt

CoRR, 2021

2020

Generative Modeling for Atmospheric Convection.

Griffin Mooers, Jens Tuyls, Stephan Mandt, Michael S. Pritchard, Tom Beucler

CoRR, 2020

Towards Physically-Consistent, Data-Driven Models of Convection.

Tom Beucler, Michael S. Pritchard, Pierre Gentine, Stephan Rasp

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Generative Modeling of Atmospheric Convection.

Griffin Mooers, Jens Tuyls, Stephan Mandt, Mike Pritchard, Tom G. Beucler

Proceedings of the CI 2020: 10th International Conference on Climate Informatics, 2020

2019

Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling.

Tom Beucler, Stephan Rasp, Michael S. Pritchard, Pierre Gentine

CoRR, 2019