YuanchenBei / Awesome-Pretraining-for-Graph-Neural-NetworksLinks
A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).
☆201Updated 7 months ago
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
Sorting:
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆227Updated last year
- ☆180Updated last year
- Accompanied repositories for our paper Graph foundation model☆215Updated 9 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆129Updated last year
- ☆90Updated last year
- List of papers on ICLR 2024☆58Updated last year
- Papers about out-of-distribution generalization on graphs.☆165Updated 2 years ago
- Official Implementation of ICLR 2024 paper "Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representat…☆236Updated 4 months ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆263Updated 8 months ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆165Updated 2 years ago
- ☆129Updated 4 months ago
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆160Updated 10 months ago
- ☆56Updated 11 months ago
- A Survey of Learning from Graphs with Heterophily☆146Updated 5 months ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆85Updated 9 months ago
- Label-free Node Classification on Graphs with Large Language Models (LLMS)☆83Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆55Updated last year
- Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs☆303Updated 5 months ago
- ☆60Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- Must-read papers on graph foundation models (GFMs)☆333Updated this week
- Papers about large graph models.☆282Updated last year
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆45Updated 8 months ago
- A curated list of papers on graph structure learning (GSL).☆49Updated 7 months ago
- Benchmark☆103Updated last year
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆37Updated last year
- A curated list of graph data augmentation papers.☆312Updated last year
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆97Updated last year