Remember our ICML25 "Graph Learning Will Lose Relevance Due To Poor Benchmarks"?
Fear no more! GraphBench is here! 🤩
We give you: The next generation of Graph Benchmarking! Including:
-New shiny high-quality datasets from diverse domains spanning seven domains, including chip design, algorithmic reasoning, and weather forecasting.
-Standardized hyperparameter tuning procedures, enabling fair and principled model comparison
- Strong, transparent baselines that accurately reflect algorithmic progress
- Comprehensive coverage of graph learning tasks, datasets, and modern GNN architectures
- Reproducibility-focused design, minimizing variance and evaluation artifacts
- Forward-looking benchmark designed for next-generation graph learning research
A huge collab with:
@chrsmrrs,
@mmbronstein,
@michael_galkin, @HolgerHoo, Timo Stoll,
@ChendiQian,
@benfinkelshtein, Ali Parvis, Darius Weber,
@ffabffrasca,
@HadarShavit,
@antoinesrdin, Arman Mielke, Marie Anastacio, Erik Müller,