YoZo-X
Pursuing a Master's degree in Control Science at UESTC, mainly researching planning, deep RL.
University of Electronic Science and Technology of China
Pinned Repositories
DeepPTZ
Code for DeepPTZ: Deep Self-Calibration for PTZ Cameras ( wacv2020 )
Deep-Reinforcement-Learning-With-Python
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
DRL-Router
DRL-Router is a method based on distributional reinforcement learning for RSP problem。
FQF-and-Extensions
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueling Networks, and parallelization.
GE-DDRL
The source code for "GE-DDRL: Graph Embedding and DeepDistributional Reinforcement Learning for ReliableShortest Path: A Universal and Scale Free Solution".
Multi-Component-Graph-Convolutional-Collaborative-Filtering
Source code for AAAI 2020 paper "Multi-Component Graph Convolutional Collaborative Filtering"
OpenCDA
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
PD-FAC
Python implement of paper "PD-FAC: Probability Density Factorized Multi-Agent Distributional Reinforcement Learning for Multi-Robot Reliable Search"
SE-GAC
SEGAC
The implementation of our SE-GAC paper.
YoZo-X's Repositories
YoZo-X/DRL-Router
DRL-Router is a method based on distributional reinforcement learning for RSP problem。
YoZo-X/PD-FAC
Python implement of paper "PD-FAC: Probability Density Factorized Multi-Agent Distributional Reinforcement Learning for Multi-Robot Reliable Search"
YoZo-X/GE-DDRL
The source code for "GE-DDRL: Graph Embedding and DeepDistributional Reinforcement Learning for ReliableShortest Path: A Universal and Scale Free Solution".
YoZo-X/Deep-Reinforcement-Learning-With-Python
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
YoZo-X/FQF-and-Extensions
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueling Networks, and parallelization.
YoZo-X/Multi-Component-Graph-Convolutional-Collaborative-Filtering
Source code for AAAI 2020 paper "Multi-Component Graph Convolutional Collaborative Filtering"
YoZo-X/OpenCDA
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.
YoZo-X/SE-GAC
YoZo-X/SEGAC
The implementation of our SE-GAC paper.