Pinned Repositories
AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
BandaidZ
BinPacking_Neural_Combinatorial_Optimization
Bin Packing Problem using Neural Combinatorial Optimization.
Bus-Trajectories-Classification
KNN classifier with DTW and LCSS algorithms
OpenCV2X
OMNeT++ V2X simulation framework for ETSI ITS-G5
OptimizationofSEandEEBasedonDRL
Optimization of SE and EE based on DRL
Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
ResourceAllocationReinforcementLearning
intial version
ResourceAllocationV2X
This project contains MATLAB codes for the paper: L. Liang, G. Y. Li, and W. Xu "Resource allocation for D2D-enabled vehicular communications," IEEE Transactions on Communications, vol. 65, no. 7, pp. 3186-3197, Jul. 2017.
tensorflow_practice
tensorflow实战练习，包括强化学习、推荐系统、nlp等
BandaidZ's Repositories
BandaidZ/OptimizationofSEandEEBasedonDRL
Optimization of SE and EE based on DRL
BandaidZ/Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
BandaidZ/ResourceAllocationReinforcementLearning
intial version
BandaidZ/ResourceAllocationV2X
This project contains MATLAB codes for the paper: L. Liang, G. Y. Li, and W. Xu "Resource allocation for D2D-enabled vehicular communications," IEEE Transactions on Communications, vol. 65, no. 7, pp. 3186-3197, Jul. 2017.
BandaidZ/tensorflow_practice
tensorflow实战练习，包括强化学习、推荐系统、nlp等
BandaidZ/AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
BandaidZ/BandaidZ
BandaidZ/BinPacking_Neural_Combinatorial_Optimization
Bin Packing Problem using Neural Combinatorial Optimization.
BandaidZ/Bus-Trajectories-Classification
KNN classifier with DTW and LCSS algorithms
BandaidZ/OpenCV2X
OMNeT++ V2X simulation framework for ETSI ITS-G5
BandaidZ/Demos
BandaidZ/flow
Computational framework for reinforcement learning in traffic control
BandaidZ/JavaGuide
「Java学习+面试指南」一份涵盖大部分Java程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！
BandaidZ/learning-to-communicate-pytorch
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
BandaidZ/MiVeCC_with_DRL
This is a Multi-intersection Vehicular Cooperative Control (MiVeCC) scheme to enable cooperation among vehicles in a 3*3 unsignalized intersections. we proposed a algorithm combined heuristic-rule and two-stage deep reinforcement learning. The heuristic-rule achieves vehicles across the intersections without collisions. Based on the heuristic-rule, DDPG is used to optimize the collaborative control of vehicles and improve the traffic efficiency. Simulation results show that the proposed algorithm can improve travel efficiency at multiple intersections by up to 4.59 times without collision compared with existing methods.
BandaidZ/ns-3_c-v2x
Cellular Vehicle-to-Everything (C-V2X) Mode 4 model for ns-3
BandaidZ/py-ransac
python implemetation of RANSAC algorithm with a line/plane fitting example.
BandaidZ/pytorch-a3c
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
BandaidZ/pytorch-madrl
PyTorch implementations of various DRL algorithms for both single agent and multi-agent.
BandaidZ/RANSAC
随机采样一致性算法，是在Ziv Yaniv的c++实现上重新实现了一次，加了中文注释，修正了一个错误。便于理解算法实现
BandaidZ/veins-lte
Veins LTE adds LTE support to Veins.
BandaidZ/WifiDemo-master
BandaidZ/WlanDqn
A dqn application for using in wlan