3 citations · 10 across the 8 of their papers we have counts for
8 papers
Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations
Rajat Kumar Sarkar, Ritam Majumdar, Vishal Jadhav +2
In Computational Fluid Dynamics (CFD), coarse mesh simulations offer computational efficiency but often lack precision. Applying conventional super-resolution to these simulations…
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…
How important are specialized transforms in Neural Operators?
Ritam Majumdar, Shirish Karande, Lovekesh Vig
Simulating physical systems using Partial Differential Equations (PDEs) has become an indispensible part of modern industrial process optimization. Traditionally, numerical solvers…
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…
DeepEpiSolver: Unravelling Inverse problems in Covid, HIV, Ebola and Disease Transmission
Ritam Majumdar, Shirish Karande, Lovekesh Vig
The spread of many infectious diseases is modeled using variants of the SIR compartmental model, which is a coupled differential equation. The coefficients of the SIR model determi…
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…
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs
Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar +3
We demonstrate a Physics-informed Neural Network (PINN) based model for real-time health monitoring of a heat exchanger, that plays a critical role in improving energy efficiency o…
Physics Informed Symbolic Networks
Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar +3
We introduce Physics Informed Symbolic Networks (PISN) which utilize physics-informed loss to obtain a symbolic solution for a system of Partial Differential Equations (PDE). Given…