hahaymm

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

bank_interview

:bank: 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）

dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

OpenHGNN

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

ClusterGCN

A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

Gadgets

Java反序列化漏洞利用链补全计划，仅用于个人归纳总结。

Representation-Learning-on-Heterogeneous-Graph

Representation-Learning-on-Heterogeneous-Graph

graph_nn

Graph Classification with Graph Convolutional Networks in PyTorch (NeurIPS 2018 Workshop)

SGCN

A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).

GAM

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

RGCN

Pytorch implementation of a RGCN Link Prediction Model

AM-GCN

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

safekit

H-GCN

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

eICU-GNN-LSTM

This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).

MySootScript

oh my soot !

temporal-gcn-lstm

Code for Characterizing and Forecasting User Engagement with In-App Action Graphs: A Case Study of Snapchat

ignnition

Framework for fast prototyping of Graph Neural Networks

GNN-NIDS

Graph-Classification-with-GCN

A simple implementation of a portion of GCN (Kipf & Welling) that can handle graph classification.

DesignPatternDemos

Java 设计模式梳理

GCN-GRU

Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data

SAGPool

使用基于自注意力池化机制结合GCN模型实现图分类

GcnLstm

KDD-2019-Hands-on

DGL tutorial in KDD 2019

GNN-in-LANL

Graph Neural Network implemented in the LANL dataset

network-security-with-STGNNs

Project for Columbia University COMSW4995 - Deep Learning.In this project we will use spatial-temporal graph neural networks (STGNNs) for anomaly detection on observed local area network traffic, with the purpose of detecting network intrusion attacks.

MyLeetCodeRecorder

记录刷过的LeetCode

JarsCounter

A tool to count classes in your jars

GNN-in-StreamSpot