Machine learning–accelerated computational fluid dynamics D Kochkov, JA Smith, A Alieva, Q Wang, MP Brenner, S Hoyer
Proceedings of the National Academy of Sciences 118 (21), e2101784118, 2021
997 2021 Neural general circulation models for weather and climate D Kochkov, J Yuval, I Langmore, P Norgaard, J Smith, G Mooers, ...
Nature 632 (8027), 1060-1066, 2024
94 2024 Learned coarse models for efficient turbulence simulation K Stachenfeld, DB Fielding, D Kochkov, M Cranmer, T Pfaff, J Godwin, ...
arXiv preprint arXiv:2112.15275, 2021
79 2021 Learned discretizations for passive scalar advection in a two-dimensional turbulent flow J Zhuang, D Kochkov, Y Bar-Sinai, MP Brenner, S Hoyer
Physical Review Fluids 6 (6), 064605, 2021
69 2021 Macroscopically Degenerate Exactly Solvable Point in the Spin- HJ Changlani, D Kochkov, K Kumar, BK Clark, E Fradkin
Physical review letters 120 (11), 117202, 2018
68 2018 Neural general circulation models D Kochkov, J Yuval, I Langmore, P Norgaard, JA Smith, G Mooers, ...
CoRR, 2023
50 2023 Learning to correct spectral methods for simulating turbulent flows G Dresdner, D Kochkov, P Norgaard, L Zepeda-Núñez, JA Smith, ...
arXiv preprint arXiv:2207.00556, 2022
50 2022 Learned simulators for turbulence K Stachenfeld, DB Fielding, D Kochkov, M Cranmer, T Pfaff, J Godwin, ...
International conference on learning representations, 2021
44 2021 Variational data assimilation with a learned inverse observation operator T Frerix, D Kochkov, J Smith, D Cremers, M Brenner, S Hoyer
International Conference on Machine Learning, 3449-3458, 2021
35 2021 Variational optimization in the AI era: Computational graph states and supervised wave-function optimization D Kochkov, BK Clark
arXiv preprint arXiv:1811.12423, 2018
35 2018 Learning ground states of quantum hamiltonians with graph networks D Kochkov, T Pfaff, A Sanchez-Gonzalez, P Battaglia, BK Clark
arXiv preprint arXiv:2110.06390, 2021
31 2021 Deviation from the dipole-ice model in the spinel spin-ice candidate D Reig-i-Plessis, SV Geldern, AA Aczel, D Kochkov, BK Clark, ...
Physical Review B 99 (13), 134438, 2019
13 2019 Classical phase diagram of the stuffed honeycomb lattice J Sahoo, D Kochkov, BK Clark, R Flint
Physical Review B 98 (13), 134419, 2018
10 2018 Disentangled sparsity networks for explainable AI M Cranmer, C Cui, DB Fielding, S Ho, A Sanchez-Gonzalez, ...
Workshop on Sparse Neural Networks 7, 2021
7 2021 Learning general-purpose cnn-based simulators for astrophysical turbulence A Sanchez-Gonzalez, K Stachenfeld, D Fielding, D Kochkov, M Cranmer, ...
ICLR 2021 SimDL Workshop, 2021
6 2021 Machine learning accelerated computational fluid dynamics A Alieva, D Kochkov, JA Smith, M Brenner, Q Wang, S Hoyer
Proceedings of the National Academy of Sciences USA, 2021
4 2021 Learning latent field dynamics of pdes D Kochkov, A Sanchez-Gonzalez, JA Smith, TJ Pfaff, P Battaglia, ...
Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020), 2020
3 2020 Neural General Circulation Models for Weather and Climate S Hoyer, J Yuval, D Kochkov, I Langmore, P Norgaard, G Mooers, ...
AGU23, 2023
2 2023 On numerical methods in quantum spin systems D Kochkov
University of Illinois at Urbana-Champaign, 2019
2 2019 Neural general circulation models optimized to predict satellite-based precipitation observations J Yuval, I Langmore, D Kochkov, S Hoyer
arXiv preprint arXiv:2412.11973, 2024
1 2024