| 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 | 589 | 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 | 117* | 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 | 25* | 2018 |
| Lower bounds over Boolean inputs for deep neural networks with ReLU gates A Mukherjee, A Basu arXiv preprint arXiv:1711.03073, 2017 | 17 | 2017 |
| Provable training of a ReLU gate with an iterative non-gradient algorithm S Karmakar, A Mukherjee Neural Networks, 2022 | 8* | 2022 |
| Depth-2 Neural Networks Under a Data-Poisoning Attack S Karmakar, A Mukherjee, T Papamarkou arXiv preprint arXiv:2005.01699, 2020 | 4 | 2020 |
| A Study of the Mathematics of Deep Learning A Mukherjee Johns Hopkins University, 2020 | 3 | 2020 |
| Capacity Bounds for the DeepONet Method of Solving Differential Equations P Gopalani, S Karmakar, A Mukherjee arXiv preprint arXiv:2205.11359, 2022 | 2 | 2022 |
| Global Convergence of SGD On Two Layer Neural Nets P Gopalani, A Mukherjee arXiv preprint arXiv:2210.11452, 2022 | 1 | 2022 |
| 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 |
| Investigating the Role of Overparameterization While Solving the Pendulum with DeepONets P Gopalani, A Mukherjee The Symbiosis of Deep Learning and Differential Equations, 2021 | | 2021 |
| Investigating the locality of neural network training dynamics S Dan, P Gampa, A Mukherjee 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 |
| N-point correlations of dark matter tracers: Renormalization with univariate biasing and its O (f_ {NL}) terms with bivariate biasing A Mukherjee arXiv preprint arXiv:1307.7714, 2013 | | 2013 |
| The Landau-Ginzburg/Calabi-Yau Phase Transition (A Review) Anirbit http://guava.physics.uiuc.edu/~nigel/courses/563/Essays_2012/PDF/Mukherjee.pdf, 2012 | | 2012 |
Amitabh BasuJohns Hopkins UniversityVerified email at jhu.edu
