Alternatives and similar repositories for SimGC

Users that are interested in SimGC are comparing it to the libraries listed below

• BangHonor / DisCo
  Official codebase for paper Disentangled Condensation for Graphs (DisCo). This codebase is based on the open-source Pytorch Geometric fra…
  ☆12Updated 7 months ago
• superallen13 / GCondenser
  ☆13Updated 3 months ago
• QueuQ / CGLB
  ☆59Updated 10 months ago
• QueuQ / SSM
  ☆10Updated 10 months ago
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆49Updated 8 months ago
• NineAbyss / ZeroG
  The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs
  ☆33Updated last year
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆119Updated 2 years ago
• CongWeilin / GraphMixer
  ☆101Updated last year
• Emory-Melody / awesome-graph-reduction
  [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
  ☆165Updated this week
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆53Updated 2 years ago
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆42Updated 2 years ago
• XYGaoG / Graph-Condensation-Papers
  Awesome Graph Condensation Papers, TKDE'25 paper: Graph Condensation: A Survey.
  ☆46Updated 2 months ago
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆85Updated 10 months ago
• MGitHubL / Awesome-Temporal-Graph-Learning
  Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
  ☆78Updated 4 months ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆92Updated 2 years ago
• Frostland12138 / Awesome-Graph-Scaling
  ☆20Updated 5 months ago
• tengxiao1 / Awesome-Graph-Contrastive-Learning-with-Heterophily
  Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
  ☆37Updated last year
• alexfanjn / Graph-Neural-Networks-With-Heterophily
  This repository contains the resources on graph neural network (GNN) considering heterophily.
  ☆263Updated 9 months ago
• usail-hkust / Awesome-Causality-Inspired-GNNs
  An awesome collection of causality-inspired graph neural networks.
  ☆83Updated 9 months ago
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆45Updated 9 months ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆56Updated last year
• CurryTang / LLMGNN
  Label-free Node Classification on Graphs with Large Language Models (LLMS)
  ☆84Updated last year
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆63Updated last year
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated 2 years ago
• RingBDStack / GC-Bench
  An Open and Unified Benchmark for Graph Condensation (submitted to NeurIPS 2024 Datasets and Benchmarks Track)
  ☆19Updated last year
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆44Updated 3 years ago
• BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
  Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
  ☆29Updated 2 years ago
• qiaoyu-tan / S2GAE
  ☆49Updated 2 years ago
• liuyang-tian / GDEM
  Implementation of ICML'24 Paper "Graph Distillation with Eigenbasis Matching"
  ☆16Updated last year
• RingBDStack / VIB-GSL
  Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022
  ☆37Updated 3 years ago