Popular GitHub Repositories for Coherence Physics

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.

A library of enterprise-grade AI agents designed to democratize artificial intelligence and provide free, open-source alternatives to overvalued Y Combinator startups. If you are excited about democratizing AI access & AI agents, please star ⭐️ this repository and use the link in the readme to join our open source AI research team.

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

robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

An open-source platform for Visual AI.

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

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

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

Adversarial skill embeddings for training reusable controllers for physically simulated characters.

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

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.

Physics-Informed Neural networks for Advanced modeling