Variational Data Assimilation with a Learned Inverse Observation Operator. - Thomas Frerix; Dmitrii Kochkov; Jamie A. Smith; Daniel Cremers; Michael P. Brenner; Stephan Hoyer (ICML, 2021)

Machine learning accelerated computational fluid dynamics. - Dmitrii Kochkov; Jamie A. Smith; Ayya Alieva; Qing Wang; Michael P. Brenner; Stephan Hoyer (CoRR, 2021)

Learning ground states of quantum Hamiltonians with graph networks. - Dmitrii Kochkov; Tobias Pfaff; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Bryan K. Clark (CoRR, 2021)

Learned Coarse Models for Efficient Turbulence Simulation. - Kimberly L. Stachenfeld; Drummond B. Fielding; Dmitrii Kochkov; Miles D. Cranmer; Tobias Pfaff; Jonathan Godwin; Can Cui; Shirley Ho; Peter W. Battaglia; Alvaro Sanchez-Gonzalez (CoRR, 2021)

Learned Simulators for Turbulence. - Kimberly L. Stachenfeld; Drummond Buschman Fielding; Dmitrii Kochkov; Miles D. Cranmer; Tobias Pfaff; Jonathan Godwin; Can Cui; Shirley Ho; Peter W. Battaglia; Alvaro Sanchez-Gonzalez (ICLR, 2022)

Neural General Circulation Models. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; James Lottes; Stephan Rasp 001; Peter D. Düben; Milan Klöwer; Sam Hatfield; Peter W. Battaglia; et al. (CoRR, 2023)

Learning to correct spectral methods for simulating turbulent flows. - Gideon Dresdner; Dmitrii Kochkov; Peter Christian Norgaard; Leonardo Zepeda-Núñez; Jamie A. Smith; Michael P. Brenner; Stephan Hoyer (Trans. Mach. Learn. Res., 2023)

Neural general circulation models optimized to predict satellite-based precipitation observations. - Janni Yuval; Ian Langmore; Dmitrii Kochkov; Stephan Hoyer (CoRR, 2024)

Neural general circulation models for weather and climate. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; Milan Klöwer; James Lottes; Stephan Rasp 001; Peter D. Düben; Sam Hatfield; Peter W. Battaglia; et al. (Nat., 2024)