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2020 – today
- 2024
[i7]Jason Stock, Jaideep Pathak, Yair Cohen, Mike Pritchard, Piyush Garg, Dale R. Durran, Morteza Mardani, Noah D. Brenowitz:
DiffObs: Generative Diffusion for Global Forecasting of Satellite Observations. CoRR abs/2404.06517 (2024)- [i6]Peter Manshausen, Yair Cohen, Jaideep Pathak, Mike Pritchard, Piyush Garg, Morteza Mardani, Karthik Kashinath, Simon Byrne, Noah D. Brenowitz:
Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales. CoRR abs/2406.16947 (2024) - 2023
- [c2]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 - [i5]Sungduk Yu, Mike Pritchard, Po-Lun Ma, Balwinder Singh, Sam Silva:
Two-step hyperparameter optimization method: Accelerating hyperparameter search by using a fraction of a training dataset. CoRR abs/2302.03845 (2023) - [i4]Morteza Mardani, Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Karthik Kashinath, Jan Kautz, Mike Pritchard:
Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. CoRR abs/2309.15214 (2023) - [i3]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) - 2021
- [i2]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) - 2020
- [j1]Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi:
A Fortran-Keras Deep Learning Bridge for Scientific Computing. Sci. Program. 2020: 8888811:1-8888811:13 (2020) - [c1]Griffin Mooers, Jens Tuyls, Stephan Mandt, Mike Pritchard, Tom G. Beucler:
Generative Modeling of Atmospheric Convection. CI 2020: 98-105 - [i1]Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi:
A Fortran-Keras Deep Learning Bridge for Scientific Computing. CoRR abs/2004.10652 (2020)
Coauthor Index
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