LeGiangK62

uav_bs_ctrl

Code implementation of "Cooperative Trajectory Design of Multiple UAV Base Stations with Heterogeneous Graph Neural Networks".

awesome-gnn-systems

A list of awesome GNN systems.

distgcn

Link Scheduling using Graph Neural Networks, IEEE TWC

GNN4Com

Graph-Neural-Network-in-wireless-communication-Papers

This repository contains list of publications on the application of Graph Neural Network in Wireless Communication

DRGO-SemCom

WMMSE-deep-unfolding

Resilient_RRM_GNN

Implementation code for the paper "Learning Resilient Radio Resource Management Policies with Graph Neural Networks" (IEEE Transactions on Signal Processing)

depth-semantic-fully-conv

PyTorch Implementation for CS231N Course Project - "Fully Convolutional Network for Depth Estimation and Semantic Segmentation"

DragGAN

Official Code for DragGAN (SIGGRAPH 2023)

Knowledge-Distillation-Paper

This resposity maintains a collection of important papers on knowledge distillation (awesome-knowledge-distillation)).

KDGA

Code for NeurIPS 2022 paper "Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks"

GNN-Resource-Management

cs224w-slides-to-code

GNNPapers

Must-read papers on graph neural networks (GNN)

GraphGym

Platform for designing and evaluating Graph Neural Networks (GNN)

PFLlib

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

ML-AndrewNg

Notebooks from the Machine Learning Specialization

pytorch_geometric

Graph Neural Network Library for PyTorch

Physics-Informed-Neural-Networks

Investigating PINNs

pytorch-beginner

pytorch tutorial for beginners

PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

DRL_RSMA_Radar_UAV

Deep-reinforcement-learning-with-pytorch

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

CRNOMA_DDPG

A DDPG based reinforcement learning algorithm for cognitive radio inspired non-orthogonal multiple access (CR-NOMA) systems

IRS-relaying

Simulation code for “Intelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?,” by Emil Björnson, Özgecan Özdogan, Erik G. Larsson, IEEE Wireless Communications Letters, vol. 9, no. 2, pp. 244-248, February 2020.