Learning on Graphs Conference 2023
LoG is an annual research conference that covers areas broadly related to machine learning on graphs and geometry, with a special focus on review quality.
27th – 30th November 2023
Virtual, free to attend
Call for Papers
The LoG Conference covers research from areas broadly related to machine learning on graphs and geometry. Registration for the virtual conference is free!
We have a proceedings track with papers published in Proceedings for Machine Learning Research (PMLR), and a non-archival extended abstract track (LaTeX style files/Overleaf template). LoG has a special focus on review quality with review constructiveness being rated by authors and area chairs. The top reviewers receive high monetary rewards!
(All deadlines are “Anywhere On Earth”.)
- August 11th, 2023: Abstract Submission Deadline (both Tracks)
- August 21st, 2023: Submission Deadline (both Tracks)
- October 7th, 2023: 2 Week Rebuttal Stage Starts
- October 20th, 2023: Rebuttal Stage Ends, Authors-Reviewers Discussion Stage Starts
- October 29th, 2023: Authors-Reviewers Discussion Stage Ends
- November 13th, 2023: Final Decisions Released
- November 20th, 2023: Camera Ready Deadline
- December 27th, 2023: Conference Starts (Virtual, free to attend)
Program Chairs
Contact PCs: pcs@logconference.org. Full program committee list.
Soledad Villar
Assistant Professor, Johns Hopkins University (JHU)
Benjamin Chamberlain
Staff Machine Learning Researcher, Twitter
Advisory Board
Regina Barzilay
Professor, Massachusetts Institute of Technology (MIT)
Xavier Bresson
Associate Professor, National University of Singapore (NUS)
Michael Bronstein
Professor, University of Oxford & Head of Graph ML, Twitter
Stephan Günnemann
Professor, Technische Universität München (TUM)
Stefanie Jegelka
Associate Professor, Massachusetts Institute of Technology (MIT)
Shuiwang Ji
Professor, Texas A&M University
Thomas Kipf
Senior Research Scientist, Google Brain
Jure Leskovec
Associate Professor, Stanford University
Pietro Liò
Full Professor, University of Cambridge
Jian Tang
Assistant Professor, HEC Montréal, Mila
Jie Tang
Professor, Tsinghua University
Petar Veličković
Staff Research Scientist, DeepMind
Soledad Villar
Assistant Professor, Johns Hopkins University (JHU)
Marinka Zitnik
Assistant Professor, Harvard University
Bastian Rieck
Principal Investigator, Institute of AI for Health, Helmholtz Munich
Razvan Pascanu
Research Scientist, DeepMind
Organizing Committee
Yuanqi Du
PhD Student, Cornell University
Hannes Stärk
PhD Student, Massachusetts Institute of Technology (MIT)
Chaitanya K. Joshi
PhD Student, University of Cambridge
Andreea Deac
PhD Student, Université de Montréal, Mila
Iulia Duta
PhD Student, University of Cambridge
Joshua Robinson
PhD Student, Massachusetts Institute of Technology (MIT)
Yanqiao Zhu
PhD Student, University of California, Los Angeles
Kexin Huang
PhD Student, Stanford University
Michelle Li
PhD Student, Harvard University
Sofia Bourhim
PhD Student, École Nationale Supérieure d’Informatique et d’Analyse des Systèmes (ENSIAS)
Ilia Igashov
PhD Student, École Polytechnique Fédérale de Lausanne (EPFL)
Alexandre Duval
PhD Student, CentraleSupelec, Université Paris-Saclay
Sponsors
To cover the costs associated with organizing a virtual, free-to-attend, and open conference, we are looking for corporate sponsors. These include costs for: Zoom, Gathertown, monetary reviewer rewards (these are unique to LoG, to incentivize high-quality reviews), and designers for our content.
Contact us at logconference@googlegroups.com if your organization is interested in sponsoring LoG!