Graph ML News (April 29th) - Upcoming ICLR and Accepted ICML papers

ICLR in Kigali starts next week! There is going to be a flurry of materials and reviews prepared by small and big labs, for instance, A Guide to ICLR 2023 — 10 Topics and 50 papers you shouldn't miss - so we’ll try to keep you updated. Meanwhile, the Machine Learning for Drug Discovery (MLDD) and ML4Materials workshops announced accepted papers - those are nice venues to see where the community moves and what would be next major conference submissions.

More resources on topology: 🍩 Database of Original & Non-Theoretical Uses of Topology (DONUT) - a collection of TDA applications beyond machine learning. TopoEmbedX - a python library for working with topological data, pretty much networkx for higher-order structures. Following that, a fresh talk on the Curvature for Graph Learning by Bastian Rieck!

Finally, ICML acceptances have arrived - some particularly interesting preprints that made it to the conference include:

- Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure
- STRIDERNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes
- MoleculeSDE - A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining (a project website so far)
- GREAD: Graph Neural Reaction-Diffusion Networks
- On the Expressive Power of Geometric GNNs
- Improved Graph HyperNetwork (GHN-3)