GraphML News (May 3rd) - The ICLR Week, new blogs

🎉 ICLR’24 starts in Vienna next Tuesday (May 5th)! There will be a ton of graph learning papers, geometric DL workshops, and, more importantly, the authors and folks who constitute the community. Michael and Chaitanya will be there, feel free to reach out to chat!

A few new blogposts:

- The TeraHAC algorithm by Google (to be presented at SIGMOD’24) for approximate clustering graphs with trillions of edges in quasi-linear time.
- Adventures of Pop – the undruggable protein by Dom Beaini (Valence Labs) - a spectacular ELI5 read about drug discovery where a celebrity protein Pop (the cause of a bad disease) has to eat a banana 🍌 (the ligand with a potential drug that would inhibit the protein). With this yummy vocabulary at hand, the post explains several key concepts like protein-ligand binding, free energy, molecular dynamics, DPMK optimization, and more.

Weekend reading:

Uncertainty for Active Learning on Graphs by Dominik Fuchsgruber, Tom Wollschläger et al feat. Stephan Günnemann (all TU Munich)

Parameter-Efficient Tuning Large Language Models for Graph Representation Learning by Qi Zhu and AWS team feat. George Karypis - on using GNNs for producing soft prompts to be sent to LLMs

4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs by Minjie Wang, Quan Gan feat. Muhan Zhang - a new benchmark for graph learning on relational DBs similar to a recent RelBench, but including more tasks like link prediction. Some GNNs seem to outperform XGBoost (Kaggle GMs are anxious and frowning)