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Jaideep Pathak
Jaideep Pathak
Bestätigte E-Mail-Adresse bei nvidia.com
Titel
Zitiert von
Zitiert von
Jahr
Model-free prediction of large spatiotemporally chaotic systems from data: A reservoir computing approach
J Pathak, B Hunt, M Girvan, Z Lu, E Ott
Physical review letters 120 (2), 024102, 2018
11322018
Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
J Pathak, Z Lu, BR Hunt, M Girvan, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (12), 2017
5822017
Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators
J Pathak, S Subramanian, P Harrington, S Raja, A Chattopadhyay, ...
arXiv preprint arXiv:2202.11214, 2022
4522022
Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics
PR Vlachas, J Pathak, BR Hunt, TP Sapsis, M Girvan, E Ott, ...
Neural Networks 126, 191-217, 2020
3992020
Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model
J Pathak, A Wikner, R Fussell, S Chandra, BR Hunt, M Girvan, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (4), 2018
3162018
Reservoir observers: Model-free inference of unmeasured variables in chaotic systems
Z Lu, J Pathak, B Hunt, M Girvan, R Brockett, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (4), 041102, 2017
3072017
A machine learning‐based global atmospheric forecast model
T Arcomano, I Szunyogh, J Pathak, A Wikner, BR Hunt, E Ott
Geophysical Research Letters 47 (9), e2020GL087776, 2020
1262020
Fourcastnet: Accelerating global high-resolution weather forecasting using adaptive fourier neural operators
T Kurth, S Subramanian, P Harrington, J Pathak, M Mardani, D Hall, ...
Proceedings of the platform for advanced scientific computing conference, 1-11, 2023
952023
Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems
A Wikner, J Pathak, B Hunt, M Girvan, T Arcomano, I Szunyogh, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (5), 2020
762020
Spherical fourier neural operators: Learning stable dynamics on the sphere
B Bonev, T Kurth, C Hundt, J Pathak, M Baust, K Kashinath, ...
International conference on machine learning, 2806-2823, 2023
612023
Using machine learning to augment coarse-grid computational fluid dynamics simulations
J Pathak, M Mustafa, K Kashinath, E Motheau, T Kurth, M Day
arXiv preprint arXiv:2010.00072, 2020
492020
A hybrid approach to atmospheric modeling that combines machine learning with a physics‐based numerical model
T Arcomano, I Szunyogh, A Wikner, J Pathak, BR Hunt, E Ott
Journal of Advances in Modeling Earth Systems 14 (3), e2021MS002712, 2022
462022
Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators, arXiv
J Pathak, S Subramanian, P Harrington, S Raja, A Chattopadhyay, ...
arXiv preprint arXiv:2202.11214, 2022
422022
Using data assimilation to train a hybrid forecast system that combines machine-learning and knowledge-based components
A Wikner, J Pathak, BR Hunt, I Szunyogh, M Girvan, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (5), 2021
412021
Using machine learning to assess short term causal dependence and infer network links
A Banerjee, J Pathak, R Roy, JG Restrepo, E Ott
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (12), 2019
372019
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
S Yu, W Hannah, L Peng, J Lin, MA Bhouri, R Gupta, B Lütjens, JC Will, ...
Advances in Neural Information Processing Systems 36, 2024
102024
Generative residual diffusion modeling for km-scale atmospheric downscaling
M Mardani, N Brenowitz, Y Cohen, J Pathak, CY Chen, CC Liu, A Vahdat, ...
arXiv preprint arXiv:2309.15214, 2023
92023
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
S Yu, WM Hannah, L Peng, MA Bhouri, R Gupta, J Lin, B Lütjens, JC Will, ...
arXiv preprint arXiv:2306.08754, 2023
92023
Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence
A Chattopadhyay, J Pathak, E Nabizadeh, W Bhimji, P Hassanzadeh
Environmental Data Science 2, e1, 2023
82023
A practical probabilistic benchmark for ai weather models
ND Brenowitz, Y Cohen, J Pathak, A Mahesh, B Bonev, T Kurth, ...
arXiv preprint arXiv:2401.15305, 2024
42024
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