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

• JHL-HUST / NAGphormer
  NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  ☆121Updated 11 months ago
• 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 last year
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆49Updated 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.
  ☆57Updated last year
• PKU-DAIR / GAMLP
  Code of GAMLP for Open Graph Benchmark. KDD‘22
  ☆61Updated 2 years ago
• GraphPKU / JacobiConv
  How Powerful are Spectral Graph Neural Networks
  ☆70Updated last year
• CongWeilin / GraphMixer
  ☆99Updated last year
• Yujun-Yan / Heterophily_and_oversmoothing
  Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
  ☆37Updated last year
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated 8 months ago
• CUAI / Non-Homophily-Large-Scale
  [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
  ☆120Updated 2 years ago
• zaixizhang / Graph_Transformer
  A pytorch implementation of graph transformer for node classification
  ☆30Updated last year
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆53Updated last year
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆76Updated 3 months ago
• flyingtango / DiGCN
  Implement of DiGCN, NeurIPS-2020
  ☆48Updated 3 years ago
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆94Updated last year
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆77Updated 3 years ago
• Oceanusity / awesome-gnns-on-large-scale-graphs
  ☆134Updated last year
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago
• EdisonLeeeee / GraphData
  A collection of graph data used for semi-supervised node classification.
  ☆38Updated 2 years ago
• jianhao2016 / GPRGNN
  ☆131Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• matthew-hirn / magnet
  MagNet graph convolutional network
  ☆36Updated last year
• yanghu819 / Graph-MLP
  ☆76Updated 3 years ago
• ChandlerBang / GCond
  [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
  ☆134Updated 3 months ago
• lgalke / lifelong-learning
  Lifelong Learning of Graph Neural Networks for Open-World Node Classification
  ☆29Updated last year
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆42Updated 2 years ago
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆107Updated last year
• THUMNLab / awesome-auto-graph-learning
  A paper collection about automated graph learning
  ☆98Updated 8 months ago
• Graph-COM / PEG
  ☆38Updated last year
• AndyJZhao / Gophormer
  ☆21Updated 2 years ago