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Announcing the Learning on Graphs Conference

A brand new venue for the Graph/Geometric Machine Learning community!

Why? See the blogpost: https://michael-bronstein.medium.com/announcing-the-learning-on-graphs-conference-c63caed7347

The LoG Conference key facts:
- Covers work broadly related to machine learning on graphs and geometry
- Proceedings track published in PMLR
- Also has a non-archival extended abstract track
- Double blind review process on OpenReview
- Top reviewers receive monetary rewards
- First year: virtual December 9-12 2022, free to attend.

Call for papers: https://logconference.github.io/cfp/

Stay updated via Twitter: https://twitter.com/LogConference
Or LinkedIn: https://www.linkedin.com/company/log-conference

Advisory board:
Regina Barzilay (MIT), Xavier Bresson (NUS), Michael Bronstein (Oxford/Twitter), Stephan Günnemann (TUM), Stefanie Jegelka (MIT), Jure Leskovec (Stanford), Pietro Liò (Cambridge), Jian Tang (MILA/HEC Montreal), Jie Tang (Tsinghua), Petar Veličković (DeepMind), Soledad Villar (JHU), Marinka Zitnik (Harvard).

Organizers:
Yuanqi Du (DP Technology), Hannes Stärk (MIT), Derek Lim (MIT), Chaitanya Joshi (Cambridge), Andreea-Ioana Deac (Mila), Iulia Duta (Cambridge), Joshua Robinson (MIT). (edited)
Medium Announcing the Learning on Graphs Conference Graph Machine Learning has become large enough of a field to deserve its own standalone event: the Learning on Graphs Conference (LoG).
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