GraphML News (Oct 21st) - Upcoming events, internships, the book on equivariance

Get ready for several upcoming graph learning events! 1️⃣ Stanford Graph Learning workshop will take place on Tuesday, Oct 24th, and its program is now available. I will give a talk introducing our new project (more on that soon) and present a poster - let’s meet if you are there 👋. 2️⃣ On Nov 8th, Molecular ML (MoML) will take place at MIT and its program with talks and posters is now available as well. Seems like the majority of posters at MoML is dedicated to generative models from three families: diffusion, flow matching, and GFlowNets.

A few LoG meetups have been announced as well. 3️⃣ LoG Madrid is planned for Nov 27-29th and accepts submissions until Nov 3rd. The venue is URJC Madrid-Arguelles Campus. 4️⃣ LoG meetup at Mila in Montreal will happen on Dec 1st.

🎓 New internship opportunities were announced from Google Research and from Google DeepMind (those are still two different entities, don’t be confused). The sooner you apply - the better.

📚 Finally, a new 524-page book on Equivariant and Coordinate Independent Convolutional Networks by Maurice Weiler ,  Patrick Forré ,  Erik Verlinde ,  and Max Welling is a monumental work on baking symmetries and equivariances into convnets. If you are fascinated by this topic, have a look at the course on Group Equivariant DL by Erik Bekkers - after a year its importance has only been growing for modern geometric DL models.

Weekend reading: still digesting ICLR submissions