
Stephan Hoyer
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DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff
Jeff Parker
Volodymyr Kuleshov
International Conference on Machine Learning (ICML) (2024)
Neural general circulation models for weather and climate
Dmitrii Kochkov
Janni Yuval
Jamie Smith
Griffin Mooers
Milan Kloewer
James Lottes
Peter Dueben
Samuel Hatfield
Peter Battaglia
Alvaro Sanchez
Matthew Willson
Nature, 632 (2024), pp. 1060-1066
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
Alex Merose
Peter Battaglia
Tyler Russell
Alvaro Sanchez
Vivian Yang
Matthew Chantry
Zied Ben Bouallegue
Peter Dueben
Carla Bromberg
Jared Sisk
Luke Barrington
Aaron Bell
arXiv (2023) (to appear)
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics
Li Li
Ryan Pederson
Ekin Dogus Cubuk
Patrick Francis Riley
Kieron Burke
Phys. Rev. Lett., 126 (2021), pp. 036401
Machine learning guided aptamer discovery
Ali Bashir
Geoff Davis
Michelle Therese Dimon
Qin Yang
Scott Ferguson
Zan Armstrong
Nature Communications (2021)
Distributed Data Processing for Large-Scale Simulations on Cloud
Lily Hu
TJ Lu
Yi-fan Chen
2021 IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY, SIGNAL & POWER INTEGRITY (2021) (to appear)
Machine learning accelerated computational fluid dynamics
Ayya Alieva
Dmitrii Kochkov
Jamie Alexander Smith
Proceedings of the National Academy of Sciences USA (2021)
Learning data-driven discretizations for partial differential equations
Yohai bar Sinai
Jason Hickey
Proceedings of the National Academy of Sciences (2019), pp. 201814058
Inundation Modeling in Data Scarce Regions
Zvika Ben-Haim
Vova Anisimov
Yusef Shafi
Sella Nevo
Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop (2019)