Alternatives and similar repositories for Graph_Transformer_Networks

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

• daiquocnguyen / Graph-Transformer
  Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
  ☆672Updated 2 years ago
• graphdeeplearning / graphtransformer
  Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
  ☆975Updated 3 years ago
• acbull / pyHGT
  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
  ☆841Updated last year
• snap-stanford / pretrain-gnns
  Strategies for Pre-training Graph Neural Networks
  ☆1,018Updated last year
• PetarV- / DGI
  Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
  ☆642Updated 2 years ago
• twjiang / graphSAGE-pytorch
  A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
  ☆652Updated last year
• weihua916 / powerful-gnns
  How Powerful are Graph Neural Networks?
  ☆1,219Updated 3 years ago
• IBM / EvolveGCN
  Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
  ☆567Updated 3 years ago
• williamleif / graphsage-simple
  Simple reference implementation of GraphSAGE.
  ☆1,022Updated 5 years ago
• RexYing / gnn-model-explainer
  gnn explainer
  ☆967Updated 9 months ago
• HazyResearch / hgcn
  Hyperbolic Graph Convolutional Networks in PyTorch.
  ☆625Updated 10 months ago
• DropEdge / DropEdge
  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
  ☆472Updated 2 years ago
• Tiiiger / SGC
  official implementation for the paper "Simplifying Graph Convolutional Networks"
  ☆843Updated 3 years ago
• ChandlerBang / awesome-self-supervised-gnn
  Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
  ☆1,681Updated last year
• acbull / GPT-GNN
  Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
  ☆492Updated 10 months ago
• RexYing / diffpool
  ☆491Updated 4 years ago
• Jhy1993 / HAN
  Heterogeneous Graph Neural Network
  ☆1,143Updated 5 years ago
• zfjsail / gae-pytorch
  Graph Auto-Encoder in PyTorch
  ☆435Updated last year
• Shen-Lab / GraphCL
  [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…
  ☆595Updated 11 months ago
• DaehanKim / vgae_pytorch
  This repository implements variational graph auto encoder by Thomas Kipf.
  ☆409Updated 3 years ago
• chennnM / GCNII
  PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
  ☆350Updated 4 years ago
• GraphSAINT / GraphSAINT
  [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive L…
  ☆488Updated 2 years ago
• jwzhanggy / Graph-Bert
  Source code of Graph-Bert
  ☆495Updated last year
• malllabiisc / CompGCN
  ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks
  ☆620Updated 10 months ago
• dsgiitr / graph_nets
  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
  ☆1,199Updated 2 months ago
• danielegrattarola / keras-gat
  Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)
  ☆488Updated 4 years ago
• iMoonLab / HGNN
  Hypergraph Neural Networks (AAAI 2019)
  ☆760Updated 2 years ago
• JiaxuanYou / graph-generation
  GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
  ☆721Updated 3 years ago
• THUDM / GraphMAE
  GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
  ☆526Updated 2 years ago
• kimiyoung / planetoid
  Semi-supervised learning with graph embeddings
  ☆921Updated 5 years ago