Popular GitHub Repositories for Physics Constrained

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

A library for scientific machine learning and physics-informed learning

Massively parallel rigidbody physics simulation on accelerator hardware.

Instant, controllable, local pre-trained AI models in Rust

robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

OpenSPG is a Knowledge Graph Engine developed by Ant Group in collaboration with OpenKG, based on the SPG (Semantic-enhanced Programmable Graph) framework. Core Capabilities: 1) domain model constrained knowledge modeling, 2) facts and logic fused representation, 3) natively support KAG...

Starter-kit to build constrained agents with Nextjs, FastAPI and Langchain

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

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

Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

An open-source platform for Visual AI.

Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Fast & Simple Resource-Constrained Learning of Deep Network Structure

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Reinforcement learning environments with musculoskeletal models

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods