Takip et
Kamyar Azizzadenesheli
Kamyar Azizzadenesheli
nvidia.com üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
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
28352020
signSGD: Compressed optimisation for non-convex problems
J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar
International Conference on Machine Learning, 560-569, 2018
12092018
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
10042023
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
864*2022
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
7562020
Stochastic activation pruning for robust adversarial defense
GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ...
International Conference on Learning Representations (ICLR) 2018, 2018
7162018
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
5262024
Physics-informed machine learning: case studies for weather and climate modelling
K Kashinath, M Mustafa, A Albert, JL Wu, C Jiang, S Esmaeilzadeh, ...
Philosophical Transactions of the Royal Society A 379 (2194), 20200093, 2021
5232021
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
Neural Information Processing Systems (Neurips) 2020, 2020
4432020
U-FNO—An enhanced Fourier neural operator-based deep-learning model for multiphase flow
G Wen, Z Li, K Azizzadenesheli, A Anandkumar, SM Benson
Advances in Water Resources 163, 104180, 2022
3882022
Neural lander: Stable drone landing control using learned dynamics
G Shi, X Shi, M O’Connell, R Yu, K Azizzadenesheli, A Anandkumar, ...
2019 International Conference on Robotics and Automation (ICRA), 9784-9790, 2019
3622019
Regularized learning for domain adaptation under label shifts
K Azizzadenesheli, A Liu, F Yang, A Anandkumar
arXiv preprint arXiv:1903.09734, 2019
2522019
signSGD with Majority Vote is Communication Efficient and Fault Tolerant
J Bernstein, J Zhao, K Azizzadenesheli, A Anandkumar
International Conference on Learning Representations (ICLR) 2019, 2018
2232018
Efficient Exploration through Bayesian Deep Q-Networks
K Azizzadenesheli, A Anandkumar
Neural Information Processing Systems (NIPS) 2017 Workshop, 2018
2152018
Neural-fly enables rapid learning for agile flight in strong winds
M O’Connell, G Shi, X Shi, K Azizzadenesheli, A Anandkumar, Y Yue, ...
Science Robotics 7 (66), eabm6597, 2022
2082022
Eikonet: Solving the eikonal equation with deep neural networks
JD Smith, K Azizzadenesheli, ZE Ross
IEEE Transactions on Geoscience and Remote Sensing 2020, 2020
1812020
Reinforcement learning of POMDPs using spectral methods
K Azizzadenesheli, A Lazaric, A Anandkumar
29th Annual Conference on Learning Theory (COLT) 2016, 2016
1562016
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
1492020
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
1362021
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ...
arXiv preprint arXiv:2307.08423, 2023
1342023
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