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Conference and Workshop Papers
- 2023
[c3]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:
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS 2023- 2020
- [c2]Griffin Mooers
, Jens Tuyls, Stephan Mandt, Mike Pritchard, Tom G. Beucler:
Generative Modeling of Atmospheric Convection. CI 2020: 98-105 - [c1]Tom Beucler, Michael S. Pritchard, Pierre Gentine, Stephan Rasp:
Towards Physically-Consistent, Data-Driven Models of Convection. IGARSS 2020: 3987-3990
Informal and Other Publications
- 2024
- [i15]Milton S. Gomez, Tom Beucler:
Lessons Learned: Reproducibility, Replicability, and When to Stop. CoRR abs/2401.03736 (2024) - [i14]Frederick Iat-Hin Tam, Tom Beucler, James H. Ruppert Jr.:
Identifying Three-Dimensional Radiative Patterns Associated with Early Tropical Cyclone Intensification. CoRR abs/2401.09493 (2024) - [i13]Monika Feldmann, Tom Beucler, Milton Gomez, Olivia Martius:
Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models. CoRR abs/2406.09474 (2024) - [i12]Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, Ryan Lagerquist:
Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications. CoRR abs/2408.02161 (2024) - 2023
- [i11]Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam, Milton S. Gomez, Jakob Runge, Andreas Gerhardus:
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery. CoRR abs/2304.05294 (2023) - [i10]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.:
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR abs/2306.08754 (2023) - [i9]Jerry Lin, Sungduk Yu, Tom Beucler, Pierre Gentine, David Walling, Mike Pritchard:
Systematic Sampling and Validation of Machine Learning-Parameterizations in Climate Models. CoRR abs/2309.16177 (2023) - [i8]Tom Beucler, Erwan Koch, Sven Kotlarski, David Leutwyler, Adrien Michel, Jonathan Koh:
Next-Generation Earth System Models: Towards Reliable Hybrid Models for Weather and Climate Applications. CoRR abs/2311.13691 (2023) - 2022
- [i7]Francesco Zanetta, Daniele Nerini, Tom Beucler, Mark A. Liniger:
Physics-constrained deep learning postprocessing of temperature and humidity. CoRR abs/2212.04487 (2022) - 2021
- [i6]Harshini Mangipudi, Griffin Mooers, Mike Pritchard, Tom Beucler, Stephan Mandt:
Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs. CoRR abs/2112.01221 (2021) - [i5]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:
Climate-Invariant Machine Learning. CoRR abs/2112.08440 (2021) - [i4]Arthur Grundner, Tom Beucler, Fernando Iglesias-Suarez, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring:
Deep Learning Based Cloud Cover Parameterization for ICON. CoRR abs/2112.11317 (2021) - 2020
- [i3]Tom Beucler, Michael S. Pritchard, Pierre Gentine, Stephan Rasp:
Towards Physically-consistent, Data-driven Models of Convection. CoRR abs/2002.08525 (2020) - [i2]Griffin Mooers, Jens Tuyls, Stephan Mandt, Michael S. Pritchard, Tom Beucler:
Generative Modeling for Atmospheric Convection. CoRR abs/2007.01444 (2020) - 2019
- [i1]Tom Beucler, Stephan Rasp, Michael S. Pritchard, Pierre Gentine:
Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling. CoRR abs/1906.06622 (2019)
Coauthor Index
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