| signSGD: Compressed optimisation for non-convex problems J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar International Conference on Machine Learning, 560-569, 2018 | 713 | 2018 |
| 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 | 699 | 2020 |
| 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 | 534 | 2018 |
| 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 | 244 | 2020 |
| 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 | 195 | 2019 |
| 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 | 161 | 2021 |
| Efficient Exploration through Bayesian Deep Q-Networks K Azizzadenesheli, A Anandkumar Neural Information Processing Systems (NIPS) 2017 Workshop, 2018 | 159 | 2018 |
| 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 | 158 | 2020 |
| 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 | 156 | 2021 |
| Regularized learning for domain adaptation under label shifts K Azizzadenesheli, A Liu, F Yang, A Anandkumar arXiv preprint arXiv:1903.09734, 2019 | 134 | 2019 |
| 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 | 131 | 2018 |
| Reinforcement learning of POMDPs using spectral methods K Azizzadenesheli, A Lazaric, A Anandkumar 29th Annual Conference on Learning Theory (COLT) 2016, 2016 | 107 | 2016 |
| 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 | 87 | 2022 |
| Eikonet: Solving the eikonal equation with deep neural networks JD Smith, K Azizzadenesheli, ZE Ross IEEE Transactions on Geoscience and Remote Sensing 2020, 2020 | 82 | 2020 |
| Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems S Lale, K Azizzadenesheli, B Hassibi, A Anandkumar Neural Information Processing Systems (Neurips) 2020, 2020 | 74 | 2020 |
| 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 | 65 | 2022 |
| Combating reinforcement learning's sisyphean curse with intrinsic fear ZC Lipton, K Azizzadenesheli, A Kumar, L Li, J Gao, L Deng arXiv preprint arXiv:1611.01211, 2016 | 64 | 2016 |
| 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 | 58 | 2021 |
| MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework CM Jiang, S Esmaeilzadeh, K Azizzadenesheli, K Kashinath, M Mustafa, ... SC20 The International Conference for High Performance Computing, Networking …, 2020 | 52 | 2020 |
| Learning causal state representations of partially observable environments A Zhang, ZC Lipton, L Pineda, K Azizzadenesheli, A Anandkumar, L Itti, ... arXiv preprint arXiv:1906.10437, 2019 | 37 | 2019 |
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
