gladisor

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

alpha-zero-general

A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

acme

A library of reinforcement learning components and agents

deepxde

A library for scientific machine learning and physics-informed learning

pfrl

PFRL: a PyTorch-based deep reinforcement learning library

reverb

Reverb is an efficient and easy-to-use data storage and transport system designed for machine learning research

ReinforcementLearning.jl

A reinforcement learning package for Julia

Dojo.jl

A differentiable physics engine for robotics

GraphNeuralNetworks.jl

Graph Neural Networks in Julia

Hyperopt.jl

Hyperparameter optimization in Julia.

MethodOfLines.jl

Automatic Finite Difference PDE solving with Julia SciML

gym3

Vectorized interface for reinforcement learning environments

gem

[NeurIPS 2021] Code for Learning Signal-Agnostic Manifolds of Neural Fields

Reinforcement-Learning-Applied-To-Metamaterial-Design

Using deep reinforcement learning to design a broadband acoustic cloak. Created under the supervision of PhD. Feruza Amirkulova and PhD Peter Gerstoft. With the help of: Linwei Zhou, Peter Lai, and Amaris De La Rosa.

pigans-material-ID

Blob-Maker

Create Blob Shapes in Python

minimal-ddpm

simple ddpm implementation