A Physics-Informed Neural Network to solve 2D steady-state heat equations.
-
Updated
Jun 30, 2024 - Jupyter Notebook
A Physics-Informed Neural Network to solve 2D steady-state heat equations.
This repository contains the source code and additional resources for the paper "Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models". The paper discusses the challenges of solar wind forecasting and the application of Physics-Informed Neural Networks (PiNNs) to improve prediction accuracy and computational efficiency.
모두를 위한 Physics-informed neural networks (PINNs)
Neural Eikonal Solver: framework for modeling traveltimes via solving eikonal equation using neural networks
A toolkit with data-driven pipelines for physics-informed machine learning.
python library for atomistic machine learning
Code of the CVPR 2024 paper "Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models"
A general PINN framework for solving ice sheet modeling
Physics-Informed Neural networks for Advanced modeling
Generative Pre-Trained Physics-Informed Neural Networks Implementation
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
This is a PINN based approach in solving high temperature heat transfer equations in manufacturing industries, with a focus on reducing the energy consumption and optimizing the sensor positioning.
Simple example of PINNs usage
This repo contains the code of my Master's Thesis. Specifically, it consists in exploring different techniques(Explanable AI, Physics Informed NN, ...) to perform State Estimation
The application of a Physics Informed Neural Network on modelling the parameters of a Continuously Stirred Tank Reactor, based on the data generated by a Simulink model.
OpenFOAM and Machine Learning Hackathon
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
Scientific Learning project on the monodomain equation
Repositorio con el material para el taller sobre PINNs en MAPI-3 2024
The Rheoinformatic lab website
Add a description, image, and links to the physics-informed-neural-networks topic page so that developers can more easily learn about it.
To associate your repository with the physics-informed-neural-networks topic, visit your repo's landing page and select "manage topics."