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Kamyar Azizzadenesheli
Kamyar Azizzadenesheli
Email confirmado em nvidia.com - Página inicial
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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
27512020
signSGD: Compressed optimisation for non-convex problems
J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar
International Conference on Machine Learning, 560-569, 2018
12012018
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
9632023
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
830*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
7412020
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
7142018
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
5132021
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
5032024
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
4382020
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
3802022
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
3582019
Regularized learning for domain adaptation under label shifts
K Azizzadenesheli, A Liu, F Yang, A Anandkumar
arXiv preprint arXiv:1903.09734, 2019
2382019
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
2202018
Efficient Exploration through Bayesian Deep Q-Networks
K Azizzadenesheli, A Anandkumar
Neural Information Processing Systems (NIPS) 2017 Workshop, 2018
2122018
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
2022022
Eikonet: Solving the eikonal equation with deep neural networks
JD Smith, K Azizzadenesheli, ZE Ross
IEEE Transactions on Geoscience and Remote Sensing 2020, 2020
1792020
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
1462020
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
1332021
U-no: U-shaped neural operators
MA Rahman, ZE Ross, K Azizzadenesheli
https://arxiv.org/pdf/2204.11127, https://arxiv.org/pdf/2204.11127, 2022
1262022
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