Alternatives and similar repositories for awesome-gnns-on-large-scale-graphs

Users that are interested in awesome-gnns-on-large-scale-graphs are comparing it to the libraries listed below

• PKU-DAIR / SGL
  A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)
  ☆155Updated last year
• PKU-DAIR / GAMLP
  Code of GAMLP for Open Graph Benchmark. KDD‘22
  ☆62Updated 3 years ago
• CUAI / Non-Homophily-Large-Scale
  [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
  ☆125Updated 3 years ago
• logseminar / Schedule
  Schedule for learning on graphs seminar
  ☆109Updated last year
• Jhy1993 / Datasets-for-Heterogeneous-Graph
  Datasets-for-Heterogeneous-Graph
  ☆134Updated 5 years ago
• sangyx / gtrick
  Bag of Tricks for Graph Neural Networks.
  ☆298Updated last year
• jianhao2016 / GPRGNN
  ☆135Updated 2 years ago
• THUDM / HGB
  Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
  ☆329Updated 2 years ago
• JHL-HUST / NAGphormer
  NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  ☆129Updated last year
• THUMNLab / awesome-auto-graph-learning
  A paper collection about automated graph learning
  ☆98Updated last year
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆165Updated 2 years ago
• GraphPKU / JacobiConv
  How Powerful are Spectral Graph Neural Networks
  ☆73Updated 2 years ago
• alexfanjn / Graph-Neural-Networks-With-Heterophily
  This repository contains the resources on graph neural network (GNN) considering heterophily.
  ☆263Updated 8 months ago
• zhao-tong / GAug
  AAAI'21: Data Augmentation for Graph Neural Networks
  ☆193Updated last year
• MIRALab-USTC / GNN-LMC
  The code of paper LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. Zhihao Shi, Xize Liang, Jie Wang. ICLR 2023…
  ☆46Updated 2 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆104Updated 2 months ago
• CUAI / Non-Homophily-Benchmarks
  [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
  ☆114Updated 3 years ago
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆81Updated 4 years ago
• snap-stanford / CAW
  ☆75Updated 2 years ago
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆119Updated 2 years ago
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆56Updated 2 years ago
• flyingdoog / PGExplainer
  Parameterized Explainer for Graph Neural Network
  ☆138Updated last year
• VITA-Group / Large_Scale_GCN_Benchmarking
  This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Trainin…
  ☆65Updated 2 years ago
• amazon-science / tgl
  ☆213Updated last year
• zwt233 / NDLS
  Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)
  ☆21Updated 3 years ago
• ICT-GIMLab / SeHGNN
  ☆115Updated last year
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆100Updated 2 years ago
• HKUST-KnowComp / NeuralSubgraphCounting
  Source Code for KDD 2020 paper "Neural Subgraph Isomorphism Counting"
  ☆54Updated last year
• doujiang-zheng / Dynamic-Temporal-Graph-Learning-Reading-List
  Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.
  ☆62Updated last year
• liun-online / HeCo
  The source code of HeCo
  ☆167Updated 3 years ago