| SegFormer: Simple and efficient design for semantic segmentation with transformers E Xie, W Wang, Z Yu, A Anandkumar, JM Alvarez, P Luo Advances in Neural Information Processing Systems 34, 12077-12090, 2021 | 2084 | 2021 |
| Tensor decompositions for learning latent variable models A Anandkumar, R Ge, D Hsu, S Kakade, M Telgarsky The Journal of Machine Learning Research 15 (1), 2773-2832, 2014 | 1306 | 2014 |
| Fourier Neural Operator for Parametric Partial Differential Equations Z Li, NB Kovachki, K Azizzadenesheli, B Lui, K Bhattacharya, A Stuart, ... International Conference on Learning Representations, 2021 | 1286 | 2021 |
| Born again neural networks T Furlanello, Z Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning, 1607-1616, 2018 | 985 | 2018 |
| signSGD: Compressed optimisation for non-convex problems J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar International Conference on Machine Learning, 560-569, 2018 | 983* | 2018 |
| Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... arXiv preprint arXiv:1803.01442, 2018 | 620 | 2018 |
| Deep active learning for named entity recognition Y Shen, H Yun, ZC Lipton, Y Kronrod, A Anandkumar arXiv preprint arXiv:1707.05928, 2017 | 494 | 2017 |
| 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 | 442* | 2020 |
| A spectral algorithm for latent dirichlet allocation A Anandkumar, DP Foster, DJ Hsu, SM Kakade, YK Liu Advances in neural information processing systems 25, 2012 | 390 | 2012 |
| Distributed algorithms for learning and cognitive medium access with logarithmic regret A Anandkumar, N Michael, AK Tang, A Swami IEEE Journal on Selected Areas in Communications 29 (4), 731-745, 2011 | 386 | 2011 |
| A method of moments for mixture models and hidden Markov models A Anandkumar, D Hsu, SM Kakade Conference on Learning Theory, 33.1-33.34, 2012 | 378 | 2012 |
| Tensorly: Tensor learning in python J Kossaifi, Y Panagakis, A Anandkumar, M Pantic arXiv preprint arXiv:1610.09555, 2016 | 362 | 2016 |
| Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014 | 336 | 2014 |
| Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs. NB Kovachki, Z Li, B Liu, K Azizzadenesheli, K Bhattacharya, AM Stuart, ... J. Mach. Learn. Res. 24 (89), 1-97, 2023 | 327* | 2023 |
| A tensor spectral approach to learning mixed membership community models A Anandkumar, R Ge, D Hsu, S Kakade Conference on Learning Theory, 867-881, 2013 | 298 | 2013 |
| Learning latent tree graphical models MJ Choi, VYF Tan, A Anandkumar, AS Willsky Journal of Machine Learning Research 12, 1771-1812, 2011 | 292 | 2011 |
| Beating the perils of non-convexity: Guaranteed training of neural networks using tensor methods M Janzamin, H Sedghi, A Anandkumar arXiv preprint arXiv:1506.08473, 2015 | 270 | 2015 |
| 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 | 259 | 2021 |
| 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 | 247 | 2019 |
| 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 | 241 | 2020 |
