Alternatives and similar repositories for powerful-gnns

Users that are interested in powerful-gnns are comparing it to the libraries listed below

• williamleif / graphsage-simple
  Simple reference implementation of GraphSAGE.
  ☆1,022Updated 5 years ago
• dsgiitr / graph_nets
  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
  ☆1,195Updated 2 months ago
• twjiang / graphSAGE-pytorch
  A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
  ☆650Updated last year
• PetarV- / DGI
  Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
  ☆641Updated 2 years ago
• Tiiiger / SGC
  official implementation for the paper "Simplifying Graph Convolutional Networks"
  ☆843Updated 3 years ago
• RexYing / diffpool
  ☆491Updated 4 years ago
• kimiyoung / planetoid
  Semi-supervised learning with graph embeddings
  ☆920Updated 5 years ago
• seongjunyun / Graph_Transformer_Networks
  Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
  ☆1,027Updated 2 years ago
• RexYing / gnn-model-explainer
  gnn explainer
  ☆957Updated 9 months ago
• zfjsail / gae-pytorch
  Graph Auto-Encoder in PyTorch
  ☆432Updated last year
• PetarV- / GAT
  Graph Attention Networks (https://arxiv.org/abs/1710.10903)
  ☆3,361Updated 3 years ago
• graphdeeplearning / benchmarking-gnns
  Repository for benchmarking graph neural networks (JMLR 2023)
  ☆2,587Updated last year
• tkipf / gae
  Implementation of Graph Auto-Encoders in TensorFlow
  ☆1,687Updated 5 years ago
• Jhy1993 / HAN
  Heterogeneous Graph Neural Network
  ☆1,140Updated 5 years ago
• snap-stanford / ogb
  Benchmark datasets, data loaders, and evaluators for graph machine learning
  ☆2,008Updated 3 weeks ago
• snap-stanford / pretrain-gnns
  Strategies for Pre-training Graph Neural Networks
  ☆1,014Updated last year
• benedekrozemberczki / ClusterGCN
  A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
  ☆799Updated 2 years ago
• JiaxuanYou / graph-generation
  GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
  ☆720Updated 3 years ago
• sungyongs / graph-based-nn
  Graph Convolutional Networks (GCNs)
  ☆916Updated 7 years ago
• shchur / gnn-benchmark
  Framework for evaluating Graph Neural Network models on semi-supervised node classification task
  ☆475Updated 6 years ago
• IBM / EvolveGCN
  Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
  ☆564Updated 3 years ago
• Diego999 / pyGAT
  Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
  ☆3,035Updated last year
• jdlc105 / Must-read-papers-and-continuous-tracking-on-Graph-Neural-Network-GNN-progress
  Papers on Graph neural network(GNN)
  ☆766Updated last year
• lightaime / deep_gcns_torch
  Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
  ☆1,160Updated 2 years ago
• benedekrozemberczki / CapsGNN
  A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
  ☆1,255Updated 2 years ago
• acbull / pyHGT
  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
  ☆834Updated last year
• DropEdge / DropEdge
  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
  ☆471Updated 2 years 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
• JiaxuanYou / P-GNN
  Position-aware Graph Neural Networks
  ☆399Updated 4 years ago
• DeepGraphLearning / GMNN
  Graph Markov Neural Networks
  ☆410Updated 4 years ago