Graph ML News (Sep 9th)

The upcoming ICLR deadline and LOG reviewing period seem to keep the community busy and reduce the amount of news content this week. We’ll compensate for that the day ICLR submissions are on OpenReview 😉

The local LoG meetup in Trento will take place on November 27th-30th (together with the main conference held online and fully remotely). There is a handful of local meetups already (if I remember correctly, other locations include UK, Germany, Canada, and a few in the US). Actually, it might be a good time for the LOG organizers to publish the confirmed ones.

The GAIN workshop on explainability and applicability of GNNs took place this week (Sept 6-8th), waiting for the recordings!

Weekend reading:

RetroBridge: Modeling Retrosynthesis with Markov Bridges by Ilia Igashov, Arne Schneuing, Marwin Segler, Michael Bronstein, Bruno Correia — a new generative framework for template-free retrosynthesis with some math traces of discrete diffusion

Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark by Jan Tönshoff, Martin Ritzert, Eran Rosenbluth, Martin Grohe — turns out some hyperparameters tinkering can boost baseline performance on LRGB!

Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks by Levy, Kaba, et al - a simple and inexpensive multi-channel trick to boost EGNNs

A few theory papers:
Representing Edge Flows on Graphs via Sparse Cell Complexes by Josef Hoppe, Michael T. Schaub

Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond by Shao et al.