Pinned Repositories
binder_test
Testing Binder tech for Jupyter notebooks
car-racing
A toolkit for testing control and planning algorithm for car racing.
casadi
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
Cheetah-Software
CMU-16745-lecture-notebooks
cmu-16745-recitations
CMU_16745_HW0_S23
CMU_16745_HW1_S23
legged_gym
Isaac Gym Environments for Legged Robots
ME331_Robot-Modeling-and-Control_project
YanzhenXiangRobotics's Repositories
YanzhenXiangRobotics/legged_gym
Isaac Gym Environments for Legged Robots
YanzhenXiangRobotics/CMU-16745-lecture-notebooks
YanzhenXiangRobotics/cmu-16745-recitations
YanzhenXiangRobotics/CMU_16745_HW0_S23
YanzhenXiangRobotics/CMU_16745_HW1_S23
YanzhenXiangRobotics/CMU_16745_HW2_S23
YanzhenXiangRobotics/daydreamer
DayDreamer: World Models for Physical Robot Learning
YanzhenXiangRobotics/DDPG-2650
YanzhenXiangRobotics/dreamer-pytorch
Dream to Control: Learning Behaviors by Latent Imagination, implemented in PyTorch.
YanzhenXiangRobotics/dreamerv2
Mastering Atari with Discrete World Models
YanzhenXiangRobotics/git_practice
A practice repo for forking and submitting pull requests
YanzhenXiangRobotics/Human-level-control-through-deep-reinforcement-learning
📖 Paper: Human-level control through deep reinforcement learning 🕹️
YanzhenXiangRobotics/IsaacGymEnvs
Isaac Gym Reinforcement Learning Environments
YanzhenXiangRobotics/ModernRobotics
Modern Robotics: Mechanics, Planning, and Control Code Library --- The primary purpose of the provided software is to be easy to read and educational, reinforcing the concepts in the book. The code is optimized neither for efficiency nor robustness.
YanzhenXiangRobotics/OmniIsaacGymEnvs
Reinforcement Learning Environments for Omniverse Isaac Gym
YanzhenXiangRobotics/OpenUSD
Universal Scene Description
YanzhenXiangRobotics/OptML_course
EPFL Course - Optimization for Machine Learning - CS-439
YanzhenXiangRobotics/oracles_and_followers
Code for the ICML 2023 paper "Oracles & Followers"
YanzhenXiangRobotics/Orbit
Unified framework for robot learning built on NVIDIA Isaac Sim
YanzhenXiangRobotics/paired
PAIRED in PyTorch 🔥
YanzhenXiangRobotics/poet
Paired Open-Ended Trailblazer (POET) and Enhanced POET
YanzhenXiangRobotics/PONG_dqn
Designed and implemented a Deep Q-Network (DQN) to autonomously learn and play the Atari game Pong. Utilized reinforcement learning principles and convolutional neural networks to process game frames and make decisions.
YanzhenXiangRobotics/pydreamer
PyTorch implementation of DreamerV2 model-based RL algorithm
YanzhenXiangRobotics/pytorch_official_examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
YanzhenXiangRobotics/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.
YanzhenXiangRobotics/reinforcement-learning-tutorials
Reinforcement Learning Algorithms Tutorial (Python)
YanzhenXiangRobotics/rocket-lander
SpaceX Falcon 9 Box2D continuous-action simulation with traditional and AI controllers.
YanzhenXiangRobotics/softlearning
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
YanzhenXiangRobotics/webpage_test
Some handy html/css/Javascript/Jquery code snippets for webpage-establishment testing purpose
YanzhenXiangRobotics/yanzhenxiangrobotics.github.io
Yanzhen Xiang | Robotics Master ETH Zurich