Tom Beucler

According to our database, Tom Beucler authored at least 17 papers between 2019 and 2024.

Collaborative distances:

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

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