This repository contains all the code and files developed for our course project "CH5710 - Applications of Machine Learning in Reaction Engineering" at IIT Madras, Department of Chemical Engineering.
Official implementation of Conflict-Free Inverse Gradients Method
Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs with JAX 📓 Check out our various notebooks to get started
UQ Group (Director: Hadi Meidani)
Improving hyperthermia treatment by controlling temperature distribution in both 1D and 2D domains and thermal energy applied to cutaneous and subcutaneous tissues, through Bio-Heat equation with Physics-Informed Neural Networks (PINNs).
PINN solver with Py Lightning and WandB
A pytorch framework for solving PDEs via Physics Informed Neural Networks (PINNs)!
PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.
Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks
PINNs/FDM for 1D/2D heat and burgers equations
This repository contains the source code for the paper: "PINNing Cerebral Blood Flow: Analysis of Perfusion MRI in Infants using Physics-Informed Neural Networks"
Replication with PyTorch of ''Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations'' by M. Raissi, P. Perdikaris, and G.E. Karniadakis from 2019.
This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.
Simple example of PINNs usage
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
Yet another PINN implementation
Add a description, image, and links to the pinns topic page so that developers can more easily learn about it.
To associate your repository with the pinns topic, visit your repo's landing page and select "manage topics."