124 citations · 218 across the 20 of their papers we have counts for
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Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp
Dibyakanti Kumar, Anirbit Mukherjee
Physics Informed Neural Networks (PINNs) have been achieving ever newer feats of solving complicated PDEs numerically while offering an attractive trade-off between accuracy and sp…
LIPEx-Locally Interpretable Probabilistic Explanations-To Look Beyond The True Class
Hongbo Zhu, Angelo Cangelosi, Procheta Sen +1
In this work, we instantiate a novel perturbation-based multi-class explanation framework, LIPEx (Locally Interpretable Probabilistic Explanation). We demonstrate that LIPEx not on…
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets
Pulkit Gopalani, Samyak Jha, Anirbit Mukherjee
In this note, we demonstrate a first-of-its-kind provable convergence of SGD to the global minima of appropriately regularized logistic empirical risk of depth nets -- for arbi…
Size Lowerbounds for Deep Operator Networks
Anirbit Mukherjee, Amartya Roy
Deep Operator Networks are an increasingly popular paradigm for solving regression in infinite dimensions and hence solve families of PDEs in one shot. In this work, we aim to esta…