| Mechanism for feature learning in neural networks and backpropagation-free machine learning models A Radhakrishnan, D Beaglehole, P Pandit, M Belkin Science 383 (6690), 1461-1467, 2024 | 92* | 2024 |
| Plug in estimation in high dimensional linear inverse problems: A rigorous analysis AK Fletcher, P Pandit, S Rangan, S Sarkar, P Schniter Journal of Statistical Mechanics: Theory and Experiment 2019 (12), 124021, 2019 | 73 | 2019 |
| Generalization error of generalized linear models in high dimensions M Emami, M Sahraee-Ardakan, P Pandit, S Rangan, A Fletcher International conference on machine learning, 2892-2901, 2020 | 60 | 2020 |
| Inference with deep generative priors in high dimensions P Pandit, M Sahraee-Ardakan, S Rangan, P Schniter, AK Fletcher IEEE Journal on Selected Areas in Information Theory 1 (1), 336-347, 2020 | 56 | 2020 |
| Benign, tempered, or catastrophic: Toward a refined taxonomy of overfitting N Mallinar, J Simon, A Abedsoltan, P Pandit, M Belkin, P Nakkiran Advances in neural information processing systems 35, 1182-1195, 2022 | 42 | 2022 |
| Benign, tempered, or catastrophic: A taxonomy of overfitting N Mallinar, JB Simon, A Abedsoltan, P Pandit, M Belkin, P Nakkiran arXiv preprint arXiv:2207.06569, 2022 | 39 | 2022 |
| Asymptotics of MAP inference in deep networks P Pandit, M Sahraee, S Rangan, AK Fletcher 2019 IEEE International Symposium on Information Theory (ISIT), 842-846, 2019 | 28 | 2019 |
| On the inconsistency of kernel ridgeless regression in fixed dimensions D Beaglehole, M Belkin, P Pandit SIAM Journal on Mathematics of Data Science 5 (4), 854-872, 2023 | 27* | 2023 |
| Toward large kernel models A Abedsoltan, M Belkin, P Pandit International Conference on Machine Learning, 61-78, 2023 | 21 | 2023 |
| Matrix inference and estimation in multi-layer models P Pandit, M Sahraee Ardakan, S Rangan, P Schniter, AK Fletcher Advances in Neural Information Processing Systems 33, 2020 | 19* | 2020 |
| Structural segmentation of Hindustani concert audio with Posterior features P Verma, TP Vinutha, P Pandit, P Rao International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015 | 18 | 2015 |
| Mechanism of feature learning in convolutional neural networks D Beaglehole, A Radhakrishnan, P Pandit, M Belkin arXiv preprint arXiv:2309.00570, 2023 | 17 | 2023 |
| Implicit bias of linear rnns M Emami, M Sahraee-Ardakan, P Pandit, S Rangan, AK Fletcher International Conference on Machine Learning, 2982-2992, 2021 | 12 | 2021 |
| Generalized autoregressive linear models for discrete high-dimensional data P Pandit, M Sahraee-Ardakan, AA Amini, S Rangan, AK Fletcher IEEE Journal on Selected Areas in Information Theory 1 (3), 884-896, 2020 | 12* | 2020 |
| Kernel methods and multi-layer perceptrons learn linear models in high dimensions M Sahraee-Ardakan, M Emami, P Pandit, S Rangan, AK Fletcher arXiv preprint arXiv:2201.08082, 2022 | 11 | 2022 |
| Refinement of the equilibrium of public goods games over networks: Efficiency and effort of specialized equilibria P Pandit, AA Kulkarni Journal of Mathematical Economics 79, 125-139, 2018 | 10 | 2018 |
| Instability and local minima in GAN training with kernel discriminators E Becker, P Pandit, S Rangan, AK Fletcher Advances in Neural Information Processing Systems 35, 20300-20312, 2022 | 9 | 2022 |
| Discount-based pricing and capacity planning for ev charging under stochastic demand P Pandit, S Coogan 2018 Annual American Control Conference (ACC), 6273-6278, 2018 | 7 | 2018 |
| Emergence in non-neural models: grokking modular arithmetic via average gradient outer product N Mallinar, D Beaglehole, L Zhu, A Radhakrishnan, P Pandit, M Belkin arXiv preprint arXiv:2407.20199, 2024 | 4 | 2024 |
| On the Nyström approximation for preconditioning in kernel machines A Abedsoltan, P Pandit, L Rademacher, M Belkin International Conference on Artificial Intelligence and Statistics, 3718-3726, 2024 | 4 | 2024 |
Sundeep RanganProfessor, ECE, New York University and Associate Director, NYU WirelessVerified email at nyu.edu
