A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).
☆215Dec 31, 2024Updated last year
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. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Awesome Papers About Performing Prompting On Graphs☆424May 15, 2025Updated last year
- A Unified Python Library for Graph Prompting☆589Jun 2, 2026Updated 2 months ago
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆255May 18, 2024Updated 2 years ago
- A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).☆46Nov 1, 2023Updated 2 years ago
- A curated list of papers on graph transfer learning (GTL).☆19Oct 23, 2023Updated 2 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- ☆194Mar 25, 2024Updated 2 years ago
- ☆22Dec 9, 2023Updated 2 years ago
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆169Oct 25, 2024Updated last year
- ☆24Sep 24, 2024Updated last year
- [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.☆188Feb 25, 2026Updated 6 months ago
- ☆108Jul 12, 2023Updated 3 years ago
- Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).☆1,728Feb 2, 2024Updated 2 years ago
- ☆19Feb 28, 2023Updated 3 years ago
- A curated list of awesome graph structure learning approaches☆43Nov 24, 2024Updated last year
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- A curated list of papers on graph structure learning (GSL).☆53Dec 31, 2024Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆26Oct 16, 2023Updated 2 years ago
- Papers about large graph models.☆291Mar 24, 2024Updated 2 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆38Sep 23, 2023Updated 2 years ago
- A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey" (TKDE)☆999Mar 2, 2025Updated last year
- A Comprehensive Benchmark of Imbalanced Graph Learning (Accepted by ICLR 2025 Spotlight)☆18Apr 17, 2025Updated last year
- ☆65Oct 24, 2022Updated 3 years ago
- A collection of AWESOME things about Graph-Related LLMs.☆2,447Nov 5, 2025Updated 9 months ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆52Dec 21, 2024Updated last year
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- A curated collection of research papers exploring the utilization of LLMs for graph-related tasks.☆656Mar 21, 2025Updated last year
- This paper is accpeted by WSDM 2023☆13Mar 13, 2023Updated 3 years ago
- Accompanied repositories for our paper Graph foundation model☆237Nov 11, 2024Updated last year
- ☆38Aug 23, 2024Updated 2 years ago
- code for kdd feasibiiity☆12Jul 17, 2023Updated 3 years ago
- ColdRec: An Open-Source Toolbox for Cold-Start Recommendation.☆117Jul 27, 2026Updated last month
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆311Mar 4, 2024Updated 2 years ago
- Papers about graph transformers.☆927Mar 19, 2025Updated last year
- Pytorch implementation for NeurIPS-23:"GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels"☆19Mar 21, 2024Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆38Oct 6, 2023Updated 2 years ago
- Benchmark☆119Apr 9, 2024Updated 2 years ago
- Awesome Few-Shot Learning on Graphs☆25Apr 27, 2025Updated last year
- ☆92Oct 23, 2023Updated 2 years ago
- A curated list of resources for graph prompting methods☆29Jan 23, 2024Updated 2 years ago
- Strategies for Pre-training Graph Neural Networks☆1,070Jul 29, 2023Updated 3 years ago
- The official implement of NeurIPS'24 Datasets and Benchmarks Track paper: GLBench: A Comprehensive Benchmark for Graphs with Large Langua…☆73Oct 28, 2024Updated last year