YuanchenBei / Awesome-Pretraining-for-Graph-Neural-NetworksLinks
A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).
☆211Updated 11 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.☆239Updated last year
- Accompanied repositories for our paper Graph foundation model☆229Updated last year
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆134Updated last year
- ☆186Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆122Updated 2 years ago
- ☆132Updated 8 months ago
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆314Updated last year
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆181Updated 2 years ago
- Papers about out-of-distribution generalization on graphs.☆168Updated 2 years ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆266Updated last year
- ☆91Updated 2 years ago
- Official Implementation of ICLR 2024 paper "Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representat…☆256Updated 8 months ago
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆163Updated last year
- Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs☆315Updated 9 months ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆48Updated last year
- Papers about large graph models.☆286Updated last year
- [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.☆172Updated last month
- Must-read papers on graph foundation models (GFMs)☆355Updated 4 months ago
- Benchmark☆109Updated last year
- ☆50Updated last year
- A Survey of Learning from Graphs with Heterophily☆154Updated 9 months ago
- List of papers on ICLR 2024☆58Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- ☆61Updated 3 years ago
- A collection of graph foundation models including papers, codes, and datasets.☆151Updated 5 months ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆101Updated last year
- ☆59Updated last year
- Label-free Node Classification on Graphs with Large Language Models (LLMS)☆90Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year