Xue Liu's repositories
alphastrassen
Reproduction of AlphaTensor paper for 2x2 matrices
Deep-Bayesian-System-Identification
This is the code for paper “Sparse BayesianDeep Learning for Dynamic System Identification”
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
DeepDPM
"DeepDPM: Deep Clustering With An Unknown Number of Clusters" [CVPR 2022]
DI-engine
OpenDILab Decision AI Engine
DOP
Codes accompanying the paper "DOP: Off-Policy Multi-Agent Decomposed Policy Gradients" (ICLR 2021, https://arxiv.org/abs/2007.12322)
ElegantRL
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
google-research
Google Research
gym-hybrid
Collection of OpenAI parametrized action-space environments.
jaxrl
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
keras-lmu3
Keras implementation of Legendre Memory Units
LEOPARD
Pytorch Implementation of 'Autonomous Cross Domain Adaptation under Extreme Label Scarcity'
MADDPG-1
Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".
MARL-Algorithms
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
prog_models
The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.
rl-starter-files
RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code
S4Torch
PyTorch implementation of Structured State Space for Sequence Modeling (S4), based on Annotated S4.
SAC-Lagrangian
PyTorch implementation of Constrained Reinforcement Learning for Soft Actor Critic Algorithm
SAC-QMIX
Algorithm that combines QMIX with SAC for Multi-Agent Reinforcement Learning.
state-spaces
Sequence Modeling with Structured State Spaces
transformer-1
A TensorFlow Implementation of the Transformer: Attention Is All You Need
transformer-2
Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.
Volt
Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
WCSAC
Code for the paper "WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning"
Youtube-Code-Repository
Repository for most of the code from my YouTube channel