What it does
Some data is best described as a graph: dots connected by lines, such as social networks, molecules or road maps. "Graph neural networks" are AI models built for this kind of data.
This project collects links to research papers on the topic from the major AI and data-mining conferences, organised by conference, year and subject.
It also links to related workshops, survey papers, books and software libraries.
Who it's for
Students and researchers studying graph neural networks.
Can I use it without coding?
Yes. It is a reading list; nothing to install. New to this? Start here.
Can I run it?
- Cost
- FreeNothing to pay or sign up for.
- Runs on
- Web browser
- Computer
- An ordinary computer is fine
- API key
- Not needed
Try it
- Open the list on GitHub and choose a conference and year.
- Browse the papers by topic and follow the links to read them.
Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?
Before you install
- Only download from the official GitHub page. Copies with similar names exist for many popular projects.
- License (MIT): Very permissive: free to use, change and share, including for business.
- More on staying safe