Anirbit Mukherjee

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 25

Top Topics

Differential Equations

Convex Minimization

Critical Points

Top Venues

Electron. Colloquium Comput. Complex.

Trans. Mach. Learn. Res.

Publications

Matteo Tucat, Anirbit Mukherjee
Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks. CoRR (2024)
Anirbit Mukherjee, Amartya Roy
Size Lowerbounds for Deep Operator Networks. Trans. Mach. Learn. Res. 2024 (2024)
Mohan Ren, Zhihao Fang, Keren Li, Anirbit Mukherjee
Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditions. CoRR (2024)
Pulkit Gopalani, Samyak Jha, Anirbit Mukherjee
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets. Trans. Mach. Learn. Res. 2024 (2024)
Sayar Karmakar, Anirbit Mukherjee, Theodore Papamarkou
Depth-2 neural networks under a data-poisoning attack. Neurocomputing 532 (2023)
Pulkit Gopalani, Samyak Jha, Anirbit Mukherjee
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets. CoRR (2023)
Anirbit Mukherjee, Amartya Roy
Size Lowerbounds for Deep Operator Networks. CoRR (2023)
Dibyakanti Kumar, Anirbit Mukherjee
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp. CoRR (2023)
Hongbo Zhu, Angelo Cangelosi, Procheta Sen, Anirbit Mukherjee
LIPEx - Locally Interpretable Probabilistic Explanations - To Look Beyond The True Class. CoRR (2023)
Pulkit Gopalani, Anirbit Mukherjee
Global Convergence of SGD On Two Layer Neural Nets. CoRR (2022)
Sayar Karmakar, Anirbit Mukherjee
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate. CoRR (2022)
Sayar Karmakar, Anirbit Mukherjee
Provable training of a ReLU gate with an iterative non-gradient algorithm. Neural Networks 151 (2022)
Pulkit Gopalani, Sayar Karmakar, Anirbit Mukherjee
Capacity Bounds for the DeepONet Method of Solving Differential Equations. CoRR (2022)
Anirbit Mukherjee
A Study of the Mathematics of Deep Learning. CoRR (2021)
Soham Dan, Phanideep Gampa, Anirbit Mukherjee
Investigating the locality of neural network training dynamics. CoRR (2021)
Anirbit Mukherjee, Ramchandran Muthukumar
Guarantees on learning depth-2 neural networks under a data-poisoning attack. CoRR (2020)
Anirbit Mukherjee, Ramchandran Muthukumar
A Study of Neural Training with Non-Gradient and Noise Assisted Gradient Methods. CoRR (2020)
Akshay Rangamani, Anirbit Mukherjee, Amitabh Basu, Ashish Arora, Tejaswini Ganapathi, Sang Peter Chin, Trac D. Tran
Sparse Coding and Autoencoders. ISIT (2018)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. ICLR (Poster) (2018)
Amitabh Basu, Soham De, Anirbit Mukherjee, Enayat Ullah
Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders. CoRR (2018)
Anirbit Mukherjee, Amitabh Basu
Lower bounds over Boolean inputs for deep neural networks with ReLU gates. CoRR (2017)
Akshay Rangamani, Anirbit Mukherjee, Ashish Arora, Tejaswini Ganapathy, Amitabh Basu, Sang Peter Chin, Trac D. Tran
Critical Points Of An Autoencoder Can Provably Recover Sparsely Used Overcomplete Dictionaries. CoRR (2017)
Anirbit Mukherjee, Amitabh Basu
Lower bounds over Boolean inputs for deep neural networks with ReLU gates. Electron. Colloquium Comput. Complex. 24 (2017)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. Electron. Colloquium Comput. Complex. 24 (2017)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. CoRR (2016)