Alternatives and similar repositories for CogDL

Users that are interested in CogDL are comparing it to the libraries listed below

• Jhy1993 / HAN
  Heterogeneous Graph Neural Network
  ☆1,155Updated 5 years ago
• snap-stanford / ogb
  Benchmark datasets, data loaders, and evaluators for graph machine learning
  ☆2,025Updated 3 months ago
• graphdeeplearning / benchmarking-gnns
  Repository for benchmarking graph neural networks (JMLR 2023)
  ☆2,617Updated 2 years ago
• shenweichen / GraphNeuralNetwork
  Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.
  ☆829Updated 2 years ago
• williamleif / graphsage-simple
  Simple reference implementation of GraphSAGE.
  ☆1,029Updated 5 years ago
• acbull / pyHGT
  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
  ☆858Updated last year
• twjiang / graphSAGE-pytorch
  A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
  ☆659Updated last year
• ChandlerBang / awesome-self-supervised-gnn
  Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
  ☆1,682Updated last year
• BUPT-GAMMA / OpenHGNN
  This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
  ☆929Updated 7 months ago
• dsgiitr / graph_nets
  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
  ☆1,210Updated 4 months ago
• CrawlScript / tf_geometric
  Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x
  ☆506Updated 7 months ago
• DeepGraphLearning / graphvite
  GraphVite: A General and High-performance Graph Embedding System
  ☆1,256Updated last year
• jdlc105 / Must-read-papers-and-continuous-tracking-on-Graph-Neural-Network-GNN-progress
  Papers on Graph neural network(GNN)
  ☆766Updated last year
• PyGCL / PyGCL
  PyGCL: A PyTorch Library for Graph Contrastive Learning
  ☆946Updated last year
• RexYing / gnn-model-explainer
  gnn explainer
  ☆987Updated 11 months ago
• kimiyoung / planetoid
  Semi-supervised learning with graph embeddings
  ☆922Updated 5 years ago
• dglai / WWW20-Hands-on-Tutorial
  Materials for DGL hands-on tutorial in WWW 2020
  ☆504Updated 4 years ago
• weihua916 / powerful-gnns
  How Powerful are Graph Neural Networks?
  ☆1,239Updated 4 years ago
• benedekrozemberczki / ClusterGCN
  A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
  ☆801Updated 2 years ago
• wangyouze / GNN-algorithms
  图神经网络相关算法详述及实现
  ☆887Updated 4 years ago
• williamleif / GraphSAGE
  Representation learning on large graphs using stochastic graph convolutions.
  ☆3,567Updated last year
• Jiakui / awesome-gcn
  resources for graph convolutional networks （图卷积神经网络相关资源）
  ☆901Updated 6 years ago
• LYuhang / GNN_Review
  GNN综述阅读报告
  ☆914Updated 4 years ago
• TrustAGI-Lab / Awesome-Graph-Neural-Networks
  Paper Lists for Graph Neural Networks
  ☆2,271Updated last year
• seongjunyun / Graph_Transformer_Networks
  Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
  ☆1,039Updated 2 years ago
• thunlp / OpenNE
  An Open-Source Package for Network Embedding (NE)
  ☆1,701Updated last year
• PetarV- / GAT
  Graph Attention Networks (https://arxiv.org/abs/1710.10903)
  ☆3,403Updated 3 years ago
• PetarV- / DGI
  Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
  ☆646Updated 2 years ago
• EdisonLeeeee / GraphGallery
  GraphGallery is a gallery for benchmarking Graph Neural Networks
  ☆468Updated 2 years ago
• awslabs / dgl-ke
  High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
  ☆1,316Updated 2 weeks ago