Popular GitHub Repositories for Quantum Dynamics

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are perfect for STEM, coding & robotics education, IoT robotics applications, AI-enhanced robotics application services, research, and DIY robotics kit development.

An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are perfect for STEM, coding & robotics education, IoT robotics applications, AI-enhanced robotics application services, research, and DIY robotics kit development.

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

Fast and Easy Infinite Neural Networks in Python

A deep learning package for many-body potential energy representation and molecular dynamics

A package for the sparse identification of nonlinear dynamical systems from data

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.

A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Computational Fluid Dynamics in JAX

SchNetPack - Deep Neural Networks for Atomistic Systems

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Generating Videos with Scene Dynamics. NIPS 2016.

End-To-End Molecular Dynamics (MD) Engine using PyTorch

Machine learning algorithms for many-body quantum systems