Alternatives and similar repositories for benchmarking-gnns

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

• snap-stanford / ogb
  Benchmark datasets, data loaders, and evaluators for graph machine learning
  ☆2,032Updated 4 months ago
• weihua916 / powerful-gnns
  How Powerful are Graph Neural Networks?
  ☆1,245Updated 4 years ago
• PetarV- / GAT
  Graph Attention Networks (https://arxiv.org/abs/1710.10903)
  ☆3,420Updated 3 years ago
• TrustAGI-Lab / Awesome-Graph-Neural-Networks
  Paper Lists for Graph Neural Networks
  ☆2,273Updated last year
• naganandy / graph-based-deep-learning-literature
  links to conference publications in graph-based deep learning
  ☆4,960Updated last week
• Diego999 / pyGAT
  Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
  ☆3,061Updated 2 years ago
• snap-stanford / GraphGym
  Platform for designing and evaluating Graph Neural Networks (GNN)
  ☆1,835Updated last year
• ChandlerBang / awesome-self-supervised-gnn
  Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
  ☆1,685Updated last year
• dsgiitr / graph_nets
  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
  ☆1,214Updated 5 months ago
• RexYing / gnn-model-explainer
  gnn explainer
  ☆997Updated last year
• THUDM / CogDL
  CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)
  ☆1,798Updated last year
• tkipf / pygcn
  Graph Convolutional Networks in PyTorch
  ☆5,348Updated 4 years ago
• williamleif / GraphSAGE
  Representation learning on large graphs using stochastic graph convolutions.
  ☆3,588Updated last year
• williamleif / graphsage-simple
  Simple reference implementation of GraphSAGE.
  ☆1,031Updated 5 years ago
• divelab / DIG
  A library for graph deep learning research
  ☆1,985Updated last year
• seongjunyun / Graph_Transformer_Networks
  Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)
  ☆1,049Updated 2 years ago
• jdlc105 / Must-read-papers-and-continuous-tracking-on-Graph-Neural-Network-GNN-progress
  Papers on Graph neural network(GNN)
  ☆767Updated 2 years ago
• snap-stanford / pretrain-gnns
  Strategies for Pre-training Graph Neural Networks
  ☆1,037Updated 2 years ago
• tkipf / gae
  Implementation of Graph Auto-Encoders in TensorFlow
  ☆1,710Updated 5 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
• lightaime / deep_gcns_torch
  Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
  ☆1,179Updated 3 years ago
• kimiyoung / planetoid
  Semi-supervised learning with graph embeddings
  ☆927Updated 5 years ago
• microsoft / Graphormer
  Graphormer is a general-purpose deep learning backbone for molecular modeling.
  ☆2,343Updated last year
• Tiiiger / SGC
  official implementation for the paper "Simplifying Graph Convolutional Networks"
  ☆845Updated 3 years ago
• microsoft / tf-gnn-samples
  TensorFlow implementations of Graph Neural Networks
  ☆926Updated 2 years ago
• graphdeeplearning / graphtransformer
  Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
  ☆996Updated 4 years ago
• twjiang / graphSAGE-pytorch
  A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
  ☆663Updated last year
• Jhy1993 / HAN
  Heterogeneous Graph Neural Network
  ☆1,165Updated 5 years ago
• acbull / pyHGT
  Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
  ☆864Updated last year
• tkipf / gcn
  Implementation of Graph Convolutional Networks in TensorFlow
  ☆7,306Updated 2 years ago