YuhangSong
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Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A generative world for general-purpose robotics & embodied AI learning.
Python Implementation of Reinforcement Learning: An Introduction
StarGAN - Official PyTorch Implementation (CVPR 2018)
Modularized Implementation of Deep RL Algorithms in PyTorch
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
RAG that intelligently adapts to your use case, data, and queries
A TensorFlow implementation of the Differentiable Neural Computer.
A starter agent that can solve a number of universe environments.
Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
Simulate electronic circuit using Python and the Ngspice / Xyce simulators
A highly-customisable gridworld game engine with some batteries included. Make your own gridworld games to test reinforcement learning agents!
A Comprehensive Reinforcement Learning Zoo for Simple Usage 🚀
An implementation of the Augmented Random Search algorithm
A simple framework for experimenting with Reinforcement Learning in Python.
Unofficial PyTorch implementation of DeepMind's PNAS 2017 paper "Overcoming Catastrophic Forgetting"
PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.
An asynchronous/parallel method of AlphaGo Zero algorithm with Gomoku
NIPS 2017 Value Prediction Network
[ECCV 2024] GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing
Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach. TPAMI 2018.
Simple grid-world environment compatible with OpenAI-gym