Project Title
GNNPapers — Curated Collection of Must-Read Graph Neural Network Papers
Overview
GNNPapers is a comprehensive repository that serves as a curated collection of must-read papers on Graph Neural Networks (GNN). It is a valuable resource for researchers, developers, and students looking to delve into the latest advancements and foundational concepts in the field of GNN. The project stands out for its structured categorization of papers into models, applications, and surveys, making it easier to navigate and find relevant research.
Key Features
- Categorized Papers: Organized into sections such as models, applications, and surveys for easy navigation.
- Broad Coverage: Includes a wide range of topics from basic models to specific applications like computer vision and natural language processing.
- Contribution by Experts: Papers are contributed and curated by leading researchers in the field, ensuring high-quality content.
Use Cases
- Research and Development: Researchers and developers use GNNPapers to stay updated with the latest research in GNN.
- Educational Purposes: Educators and students utilize the repository as a learning tool to understand the theoretical and practical aspects of GNN.
- Industry Applications: Professionals in various industries apply insights from these papers to develop GNN-based solutions for real-world problems.
Advantages
- Comprehensive Collection: Offers a one-stop repository for the most influential and important papers in GNN.
- Structured Organization: Makes it easy for users to find specific types of research or applications of interest.
- Community-Driven: Continuously updated and expanded by contributions from the community of GNN researchers.
Limitations / Considerations
- No Direct Implementations: While the repository provides papers, it does not offer direct code implementations, which might be desired by some practitioners.
- License Information Unknown: The license under which the repository operates is not specified, which could be a consideration for commercial use.
Similar / Related Projects
- Papers With Code: A platform that provides a collection of papers with corresponding code implementations, differing from GNNPapers by offering a more practical, code-focused approach.
- Graph Neural Network GitHub: Another repository focusing on GNN, but with a different set of papers and possibly a different curation philosophy.
- Awesome Graph Neural Networks: A curated list of resources on GNN, which may offer a broader range of materials but might not be as focused as GNNPapers.
Basic Information
- GitHub: https://github.com/thunlp/GNNPapers
- Stars: 16,534
- License: Unknown
- Last Commit: 2025-08-19
📊 Project Information
- Project Name: GNNPapers
- GitHub URL: https://github.com/thunlp/GNNPapers
- Programming Language: Unknown
- ⭐ Stars: 16,534
- 🍴 Forks: 3,020
- 📅 Created: 2018-12-24
- 🔄 Last Updated: 2025-08-19
🏷️ Project Topics
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