Popular GitHub Repositories for Dynamics Variation

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.

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.

Fast and Easy Infinite Neural Networks in Python

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

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

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Flowtron is an auto-regressive flow-based generative network for text to speech synthesis with control over speech variation and style transfer

Computational Fluid Dynamics in JAX

SchNetPack - Deep Neural Networks for Atomistic Systems

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

PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Unofficial PyTorch implementation of the paper titled "Progressive growing of GANs for improved Quality, Stability, and Variation"

Code for our paper "Hamiltonian Neural Networks"

Differentiable Fluid Dynamics Package

Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"