kanhaiya-gupta/pinn-research-platform

A comprehensive research platform for Physics-Informed Neural Networks (PINNs) featuring 10+ applications including forward/inverse problems, data assimilation, and scientific discovery with interactive web interface.

34
/ 100
Emerging

This platform helps researchers and scientists model complex physical systems by using data and scientific laws together. You provide known physical equations and observational data, and it generates predictions or uncovers hidden parameters for various scientific applications through an interactive web interface. It's designed for physicists, engineers, and researchers working with physics-informed machine learning.

Use this if you need to solve forward or inverse problems, perform data assimilation, quantify uncertainties, or discover new physical laws using Physics-Informed Neural Networks.

Not ideal if you are looking for a general-purpose machine learning framework without specific physics integration or if your problems don't involve differential equations.

physics-modeling computational-engineering scientific-discovery data-assimilation uncertainty-quantification
No License No Package No Dependents
Maintenance 10 / 25
Adoption 4 / 25
Maturity 7 / 25
Community 13 / 25

How are scores calculated?

Stars

8

Forks

2

Language

Python

License

Last pushed

Feb 21, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/kanhaiya-gupta/pinn-research-platform"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.