Mike Pritchard

12 papers A* 1Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting. CoRR Jean Kossaifi, Nikola B. Kovachki, Morteza Mardani, Daniel V. Leibovici, Suman Ravuri, Ira Shokar, Edoardo Calvello, Mohammad Shoaib Abbas, Peter Harrington, Ashay Subramaniam, Noah D. Brenowitz, Boris Bonev, Wonmin Byeon, Karsten Kreis, Dale R. Durran, Arash Vahdat, Mike Pritchard, Jan Kautz
2025	J	`jnl`	Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a $50,000 Kaggle Competition. CoRR 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
2024	J	`jnl`	DiffObs: Generative Diffusion for Global Forecasting of Satellite Observations. CoRR Jason Stock, Jaideep Pathak, Yair Cohen, Mike Pritchard, Piyush Garg, Dale R. Durran, Morteza Mardani, Noah D. Brenowitz
2024	J	`jnl`	Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales. CoRR Peter Manshausen, Yair Cohen, Jaideep Pathak, Mike Pritchard, Piyush Garg, Morteza Mardani, Karthik Kashinath, Simon Byrne, Noah D. Brenowitz
2023	A*	`conf`	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS 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
2023	J	`jnl`	Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. CoRR Morteza Mardani, Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Karthik Kashinath, Jan Kautz, Mike Pritchard
2023	J	`jnl`	Systematic Sampling and Validation of Machine Learning-Parameterizations in Climate Models. CoRR Jerry Lin, Sungduk Yu, Tom Beucler, Pierre Gentine, David Walling, Mike Pritchard
2023	J	`jnl`	Two-step hyperparameter optimization method: Accelerating hyperparameter search by using a fraction of a training dataset. CoRR Sungduk Yu, Mike Pritchard, Po-Lun Ma, Balwinder Singh, Sam Silva
2021	J	`jnl`	Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs. CoRR Harshini Mangipudi, Griffin Mooers, Mike Pritchard, Tom Beucler, Stephan Mandt
2020	J	`jnl`	A Fortran-Keras Deep Learning Bridge for Scientific Computing. CoRR Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi
2020	J	`jnl`	A Fortran-Keras Deep Learning Bridge for Scientific Computing. Sci. Program. Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi
2020	—	`conf`	Generative Modeling of Atmospheric Convection. CI Griffin Mooers, Jens Tuyls, Stephan Mandt, Mike Pritchard, Tom G. Beucler