Understanding deep neural networks with rectified linear units R Arora, A Basu, P Mianjy, A Mukherjee The International Conference on Learning Representations (ICLR) 2018, 2016 | 750 | 2016 |
Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders S De, A Mukherjee, E Ullah arXiv preprint arXiv:1807.06766, 2018 | 143* | 2018 |
Sparse coding and autoencoders A Rangamani, A Mukherjee, A Basu, A Arora, T Ganapathi, S Chin, ... 2018 IEEE International Symposium on Information Theory (ISIT), 36-40, 2018 | 28* | 2018 |
Lower bounds over Boolean inputs for deep neural networks with ReLU gates A Mukherjee, A Basu arXiv preprint arXiv:1711.03073, 2017 | 22 | 2017 |
Provable training of a ReLU gate with an iterative non-gradient algorithm S Karmakar, A Mukherjee Neural Networks, 2022 | 11* | 2022 |
Depth-2 neural networks under a data-poisoning attack S Karmakar, A Mukherjee, T Papamarkou Neurocomputing 532, 56-66, 2023 | 5 | 2023 |
A Study of the Mathematics of Deep Learning A Mukherjee Johns Hopkins University, 2020 | 5 | 2020 |
Towards Size-Independent Generalization Bounds for Deep Operator Nets P Gopalani, S Karmakar, D Kumar, A Mukherjee arXiv preprint arXiv:2205.11359, 2022 | 3* | 2022 |
Global Convergence of SGD On Two Layer Neural Nets P Gopalani, A Mukherjee arXiv preprint arXiv:2210.11452, 2022 | 2 | 2022 |
Size Lowerbounds for Deep Operator Networks A Mukherjee, A Roy Transactions on Machine Learning Research, 2024 | 1 | 2024 |
Investigating the Role of Overparameterization While Solving the Pendulum with DeepONets P Gopalani, A Mukherjee The Symbiosis of Deep Learning and Differential Equations, 2021 | 1 | 2021 |
Investigating the Ability of PINNs to Solve Burgers’ PDE Near Finite-Time Blowup D Kumar, A Mukherjee Machine Learning: Science and Technology 5 (2), 025063, 2024 | | 2024 |
Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks M Tucat, A Mukherjee arXiv preprint arXiv:2404.08624, 2024 | | 2024 |
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets P Gopalani, S Jha, A Mukherjee Transactions on Machine Learning Research, 2024 | | 2024 |
LIPEx--Locally Interpretable Probabilistic Explanations--To Look Beyond The True Class H Zhu, A Cangelosi, P Sen, A Mukherjee arXiv preprint arXiv:2310.04856, 2023 | | 2023 |
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate S Karmakar, A Mukherjee arXiv preprint arXiv:2204.12554, 2022 | | 2022 |
Dynamics of Local Elasticity During Training of Neural Nets S Dan, A Mukherjee, A Das, P Gampa arXiv preprint arXiv:2111.01166, 2021 | | 2021 |
Identifying stochastic oracles for fast convergence of RMSProp AM Jiayao Zhang Deep Math 2020, 2020 | | 2020 |
Improving PAC-Bayes bounds on risk of neural nets using geometrical properties of training A Mukherjee, D Roy, P Rastogi, J Yang ICML 2019 Workshop, Understanding and Improving Generalization in Deep Learning, 2019 | | 2019 |
Renyi entropy of the critical O (N) model A Mukherjee arXiv preprint arXiv:1512.01226, 2015 | | 2015 |