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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
5862020
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
2112020
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
1432020
Model reduction and neural networks for parametric PDEs
K Bhattacharya, B Hosseini, NB Kovachki, AM Stuart
arXiv preprint arXiv:2005.03180, 2020
1382020
Neural operator: Learning maps between function spaces
N Kovachki, Z Li, B Liu, K Azizzadenesheli, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2108.08481, 2021
1242021
Ensemble Kalman inversion: a derivative-free technique for machine learning tasks
NB Kovachki, AM Stuart
Inverse Problems 35 (9), 095005, 2019
862019
On universal approximation and error bounds for fourier neural operators
N Kovachki, S Lanthaler, S Mishra
The Journal of Machine Learning Research 22 (1), 13237-13312, 2021
572021
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
512019
Physics-informed neural operator for learning partial differential equations
Z Li, H Zheng, N Kovachki, D Jin, H Chen, B Liu, K Azizzadenesheli, ...
arXiv preprint arXiv:2111.03794, 2021
482021
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
272020
Fourier neural operator for parametric partial differential equations (2020)
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2010.08895, 2010
202010
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
192022
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, 2021
192021
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
182022
B. liu, K. Bhattacharya, A. Stuart, and A. Anandkumar, Fourier neural operator for parametric partial differential equations
Z Li, NB Kovachki, K Azizzadenesheli
International Conference on Learning Representations, 1, 2021
182021
Continuous time analysis of momentum methods
NB Kovachki, AM Stuart
The Journal of Machine Learning Research 22 (1), 760-799, 2021
182021
Markov neural operators for learning chaotic systems
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2106.06898, 2021
172021
Conditional sampling with monotone GANs
N Kovachki, R Baptista, B Hosseini, Y Marzouk
arXiv preprint arXiv:2006.06755, 2020
172020
Convergence rates for learning linear operators from noisy data
MV de Hoop, NB Kovachki, NH Nelsen, AM Stuart
arXiv preprint arXiv:2108.12515, 2021
132021
Analysis of momentum methods
NB Kovachki, AM Stuart
arXiv, 2019
102019
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