Popular GitHub Repositories for Telegraph Equation

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Distributed High-Performance Symbolic Regression in Julia

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Physics-Informed Neural networks for Advanced modeling

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

ANI-1 neural net potential with python interface (ASE)

[ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large Language Models

A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs

A pytorch implementaion of physics informed neural networks for two dimensional NS equation

A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.

A Physics-Informed Neural Network to solve 2D steady-state heat equations.

C# math expression library with symbolic computation support

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Generative Pre-Trained Physics-Informed Neural Networks Implementation

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

This is the official repo for the paper "LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models"