Alternatives and similar repositories for Awesome-Pretraining-for-Graph-Neural-Networks

Users that are interested in Awesome-Pretraining-for-Graph-Neural-Networks are comparing it to the libraries listed below

• LechengKong / OneForAll
  A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.
  ☆239Updated last year
• HaitaoMao / Awesome_Graph_Foundation_Models
  Accompanied repositories for our paper Graph foundation model
  ☆228Updated last year
• SitaoLuan / LLM4Graph
  ☆186Updated last year
• JHL-HUST / NAGphormer
  NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
  ☆132Updated last year
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆121Updated 2 years ago
• THUDM / GraphMAE2
  GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23
  ☆176Updated 2 years ago
• AndyJZhao / GLEM
  ☆131Updated 8 months ago
• CurryTang / Towards-graph-foundation-models
  ☆91Updated 2 years ago
• alexfanjn / Graph-Neural-Networks-With-Heterophily
  This repository contains the resources on graph neural network (GNN) considering heterophily.
  ☆264Updated last year
• THUMNLab / awesome-graph-ood
  Papers about out-of-distribution generalization on graphs.
  ☆167Updated 2 years ago
• MingChen-Sun / GPPT
  ☆61Updated 3 years ago
• Starlien95 / GraphPrompt
  GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks
  ☆162Updated last year
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆47Updated 11 months ago
• XiaoxinHe / TAPE
  Official Implementation of ICLR 2024 paper "Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representat…
  ☆254Updated 7 months ago
• CurryTang / LLMGNN
  Label-free Node Classification on Graphs with Large Language Models (LLMS)
  ☆87Updated 2 years ago
• CurryTang / Graph-LLM
  Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
  ☆310Updated 8 months ago
• XiaoxinHe / iclr2024_learning_on_graphs
  List of papers on ICLR 2024
  ☆58Updated last year
• CUAI / Non-Homophily-Large-Scale
  [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
  ☆124Updated 3 years ago
• THUMNLab / awesome-large-graph-model
  Papers about large graph models.
  ☆286Updated last year
• Zehong-Wang / Awesome-Foundation-Models-on-Graphs
  A collection of graph foundation models including papers, codes, and datasets.
  ☆139Updated 4 months ago
• Emory-Melody / awesome-graph-reduction
  [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.
  ☆168Updated 3 weeks ago
• GSL-Benchmark / GSLB
  A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)
  ☆121Updated last year
• BUPT-GAMMA / GFMPapers
  Must-read papers on graph foundation models (GFMs)
  ☆355Updated 3 months ago
• sktsherlock / TAG-Benchmark
  Benchmark
  ☆106Updated last year
• gongchenghua / Papers-Graphs-with-Heterophily
  A Survey of Learning from Graphs with Heterophily
  ☆153Updated 9 months ago
• qitianwu / NodeFormer
  The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…
  ☆313Updated last year
• YangLing0818 / VQGraph
  [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
  ☆103Updated last year
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆56Updated last year
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆87Updated last year
• Juanhui28 / HeaRT
  ☆59Updated last year