A library for scientific machine learning and physics-informed learning

Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]

physics-informed neural network for elastodynamics problem

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Generative Pre-Trained Physics-Informed Neural Networks Implementation

Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.

NVFi in PyTorch (NeurIPS 2023)

Physics-informed deep super-resolution of spatiotemporal data

Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

Source code for Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning

Official Implementation of Integrating Physics-Informed Vectors for Improved Wind Speed Forecasting with Neural Networks

Code for the NeurIPS 2021 paper "Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features"

Official implementation of Towards Learning Monocular 3D Object Localization From 2D Labels Using the Physical Laws of Motion

Repository for NeurIPS 2025 paper, "Physics-informed Reduced Order Modeling of Time-dependent PDEs via Differentiable Solvers."

Official imprementation of the paper "A general deep learning method for computing molecular parameters of viscoelastic constitutive model by solving an inverse problem"

Source code of paper "Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling".

PINEURODEs is a repository collecting CMS group research work on the application of neural (stochastic/ordinary) differential equations and physically-informed neural networks to model complex multiscale systems.

Lorentz-equivariant Transformer based on Lorentz Local Canonicalization (Spinner et al. 2025)

Exploring the concepts of Physics Informed Neural Networks. Coding a Physics Informed Neural Network to simulate a harmonic oscillator and solve a simple first-order ordinary differential equation.

This repositey includes all files and scripts related to the project "Automated Materials Testing Analyzer with Stress-Strain Visualizer". This repo includes Python scripts and an Excel file, where the Python scripts are used in the excel file to automate mundane data tasks.