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Nikola Kovachki
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Fourier neural operator for parametric partial differential equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2010.08895, 2020
26252020
Neural operator: Learning maps between function spaces with applications to pdes
N Kovachki, Z Li, B Liu, K Azizzadenesheli, K Bhattacharya, A Stuart, ...
Journal of Machine Learning Research 24 (89), 1-97, 2023
9172023
Neural operator: Graph kernel network for partial differential equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2003.03485, 2020
7252020
Physics-informed neural operator for learning partial differential equations
Z Li, H Zheng, N Kovachki, D Jin, H Chen, B Liu, K Azizzadenesheli, ...
ACM/JMS Journal of Data Science 1 (3), 1-27, 2024
4872024
Multipole graph neural operator for parametric partial differential equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, A Stuart, K Bhattacharya, ...
Advances in Neural Information Processing Systems 33, 6755-6766, 2020
4232020
Model reduction and neural networks for parametric PDEs
K Bhattacharya, B Hosseini, NB Kovachki, AM Stuart
The SMAI journal of computational mathematics 7, 121-157, 2021
4102021
On universal approximation and error bounds for Fourier neural operators
N Kovachki, S Lanthaler, S Mishra
Journal of Machine Learning Research 22 (290), 1-76, 2021
2922021
Ensemble Kalman inversion: a derivative-free technique for machine learning tasks
NB Kovachki, AM Stuart
Inverse Problems 35 (9), 095005, 2019
1582019
Neural operator: Graph kernel network for partial differential equations
A Anandkumar, K Azizzadenesheli, K Bhattacharya, N Kovachki, Z Li, ...
ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020
1422020
Fourier neural operator for parametric partial differential equations, arXiv
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2010.08895, 2020
1282020
Burigede liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar. Fourier neural operator for parametric partial differential equations
Z Li, NB Kovachki, K Azizzadenesheli
International Conference on Learning Representations 2 (3), 4, 2021
1272021
Neural operators for accelerating scientific simulations and design
K Azizzadenesheli, N Kovachki, Z Li, M Liu-Schiaffini, J Kossaifi, ...
Nature Reviews Physics, 1-9, 2024
1012024
A learning-based multiscale method and its application to inelastic impact problems
B Liu, N Kovachki, Z Li, K Azizzadenesheli, A Anandkumar, AM Stuart, ...
Journal of the Mechanics and Physics of Solids 158, 104668, 2022
792022
Geometry-informed neural operator for large-scale 3d pdes
Z Li, N Kovachki, C Choy, B Li, J Kossaifi, S Otta, MA Nabian, M Stadler, ...
Advances in Neural Information Processing Systems 36, 2024
712024
Regression clustering for improved accuracy and training costs with molecular-orbital-based machine learning
L Cheng, NB Kovachki, M Welborn, TF Miller III
Journal of Chemical Theory and Computation 15 (12), 6668-6677, 2019
692019
Convergence rates for learning linear operators from noisy data
MV de Hoop, NB Kovachki, NH Nelsen, AM Stuart
SIAM/ASA Journal on Uncertainty Quantification 11 (2), 480-513, 2023
672023
Multiscale modeling of materials: Computing, data science, uncertainty and goal-oriented optimization
N Kovachki, B Liu, X Sun, H Zhou, K Bhattacharya, M Ortiz, A Stuart
Mechanics of Materials 165, 104156, 2022
482022
Markov neural operators for learning chaotic systems
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2106.06898, 2-3, 2021
482021
Operator learning: Algorithms and analysis
NB Kovachki, S Lanthaler, AM Stuart
arXiv preprint arXiv:2402.15715, 2024
452024
Score-based diffusion models in function space
JH Lim, NB Kovachki, R Baptista, C Beckham, K Azizzadenesheli, ...
arXiv preprint arXiv:2302.07400, 2023
392023
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