Alternatives and similar repositories for Scaling-Up-Graph-Neural-Networks-Via-Graph-Coarsening

Users that are interested in Scaling-Up-Graph-Neural-Networks-Via-Graph-Coarsening are comparing it to the libraries listed below

• yule-BUAA / DyGLib
  A Library for Dynamic Graph Learning (NeurIPS 2023)
  ☆276Updated 2 years ago
• CUAI / Non-Homophily-Large-Scale
  [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
  ☆124Updated 3 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆105Updated 5 months ago
• CongWeilin / GraphMixer
  ☆104Updated 2 years ago
• PKU-DAIR / SGL
  A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)
  ☆157Updated last year
• Oceanusity / awesome-gnns-on-large-scale-graphs
  ☆138Updated 2 years ago
• 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.
  ☆63Updated 2 years ago
• snap-stanford / roland
  ☆142Updated 2 years ago
• jianhao2016 / GPRGNN
  ☆139Updated 2 years ago
• qitianwu / NodeFormer
  The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…
  ☆314Updated last year
• ChandlerBang / GCond
  [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"
  ☆141Updated 2 months ago
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆52Updated 2 years ago
• GraphPKU / JacobiConv
  How Powerful are Spectral Graph Neural Networks
  ☆74Updated 2 years ago
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆121Updated 2 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
• fpour / DGB
  Dynamic Graph Benchmark
  ☆87Updated 2 years ago
• ZhenyuYangMQ / Awesome-Graph-Level-Learning
  Awesome graph-level learning methods. Collections of commonly used datasets, papers as well as implementations are listed in this github …
  ☆59Updated last year
• LiuChuang0059 / graph-pooling-papers
  IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
  ☆117Updated 8 months ago
• JHL-HUST / NAGphormer
  NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  ☆132Updated last year
• flyingdoog / PGExplainer
  Parameterized Explainer for Graph Neural Network
  ☆140Updated last year
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated last year
• GemsLab / CPGNN
  ☆29Updated 4 years ago
• Emory-Melody / awesome-graph-reduction
  [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
  ☆171Updated last month
• loukasa / graph-coarsening
  Multilevel graph coarsening algorithm with spectral and cut guarantees
  ☆91Updated 5 years ago
• amazon-science / tgl
  ☆216Updated last year
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆104Updated 2 years ago
• zhao-tong / GAug
  AAAI'21: Data Augmentation for Graph Neural Networks
  ☆195Updated last year
• THUMNLab / awesome-auto-graph-learning
  A paper collection about automated graph learning
  ☆97Updated last year
• Yujun-Yan / Heterophily_and_oversmoothing
  Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
  ☆41Updated 2 years ago
• PKU-DAIR / GAMLP
  Code of GAMLP for Open Graph Benchmark. KDD‘22
  ☆63Updated 3 years ago