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.
  ☆1,025Updated 5 years ago
• Tiiiger / SGC
  official implementation for the paper "Simplifying Graph Convolutional Networks"
  ☆842Updated 3 years ago
• RexYing / diffpool
  ☆492Updated 4 years ago
• RexYing / gnn-model-explainer
  gnn explainer
  ☆977Updated 10 months ago
• seongjunyun / Graph_Transformer_Networks
  Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
  ☆1,035Updated 2 years ago
• snap-stanford / pretrain-gnns
  Strategies for Pre-training Graph Neural Networks
  ☆1,022Updated last year
• PetarV- / DGI
  Deep Graph Infomax (https://arxiv.org/abs/1809.10341)
  ☆644Updated 2 years ago
• jdlc105 / Must-read-papers-and-continuous-tracking-on-Graph-Neural-Network-GNN-progress
  Papers on Graph neural network(GNN)
  ☆766Updated last year
• kimiyoung / planetoid
  Semi-supervised learning with graph embeddings
  ☆921Updated 5 years ago
• twjiang / graphSAGE-pytorch
  A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
  ☆653Updated last year
• dsgiitr / graph_nets
  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
  ☆1,203Updated 3 months ago
• graphdeeplearning / benchmarking-gnns
  Repository for benchmarking graph neural networks (JMLR 2023)
  ☆2,601Updated 2 years ago
• 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
• snap-stanford / ogb
  Benchmark datasets, data loaders, and evaluators for graph machine learning
  ☆2,012Updated 2 months ago
• JiaxuanYou / graph-generation
  GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
  ☆722Updated 3 years ago
• sungyongs / graph-based-nn
  Graph Convolutional Networks (GCNs)
  ☆919Updated 7 years ago
• acbull / pyHGT
  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
  ☆846Updated last year
• DropEdge / DropEdge
  This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
  ☆472Updated 2 years ago
• JiaxuanYou / P-GNN
  Position-aware Graph Neural Networks
  ☆399Updated 4 years ago
• shchur / gnn-benchmark
  Framework for evaluating Graph Neural Network models on semi-supervised node classification task
  ☆475Updated 6 years ago
• tkipf / gae
  Implementation of Graph Auto-Encoders in TensorFlow
  ☆1,699Updated 5 years ago
• DeepGraphLearning / GMNN
  Graph Markov Neural Networks
  ☆410Updated 5 years ago
• danielegrattarola / keras-gat
  Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)
  ☆490Updated 4 years ago
• benedekrozemberczki / SimGNN
  A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
  ☆795Updated 2 years ago
• benedekrozemberczki / CapsGNN
  A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
  ☆1,260Updated 2 years ago
• inyeoplee77 / SAGPool
  Official PyTorch Implementation of SAGPool - ICML 2019
  ☆369Updated last year
• HazyResearch / hgcn
  Hyperbolic Graph Convolutional Networks in PyTorch.
  ☆629Updated 11 months ago
• daiquocnguyen / Graph-Transformer
  Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
  ☆673Updated 2 years ago
• matenure / FastGCN
  The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""
  ☆526Updated 4 years ago
• Jhy1993 / HAN
  Heterogeneous Graph Neural Network
  ☆1,147Updated 5 years ago