activity
20162026
most citedLayer-wise training of deep networks using kernel similarity

16 citations · 37 across the 25 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Towards Mitigating Perceived Unfairness in Contracts from a Non-Legal Stakeholder's Perspective

Anmol Singhal, Preethu Rose Anish, Shirish Karande +1

Commercial contracts are known to be a valuable source for deriving project-specific requirements. However, contract negotiations mainly occur among the legal counsel of the partie…

cs.LG2023

Can Physics Informed Neural Operators Self Improve?

Ritam Majumdar, Amey Varhade, Shirish Karande +1

Self-training techniques have shown remarkable value across many deep learning models and tasks. However, such techniques remain largely unexplored when considered in the context o…

cs.LG2023★ 1 cited

HyperLoRA for PDEs

Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar +3

Physics-informed neural networks (PINNs) have been widely used to develop neural surrogates for solutions of Partial Differential Equations. A drawback of PINNs is that they have t…

cs.AI2023

Synthesis of Mathematical programs from Natural Language Specifications

Ganesh Prasath, Shirish Karande

Several decision problems that are encountered in various business domains can be modeled as mathematical programs, i.e. optimization problems. The process of conducting such model…

cs.LG2023★ 2 cited

Symbolic Regression for PDEs using Pruned Differentiable Programs

Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar +3

Physics-informed Neural Networks (PINNs) have been widely used to obtain accurate neural surrogates for a system of Partial Differential Equations (PDE). One of the major limitatio…