Learning on Graphs Conference 2025
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.
TBD 2025
UCLA, Los Angeles
Community: Slack
What is LoG?
Coming Soon!
The LoG Conference covers research from areas broadly related to machine learning on graphs and geometry.
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!
Local Meetups
On previous years, at the same time as the main virtual event, the LoG community hosted a ‘network’ of local mini-conferences around the world. The objective is to connect participants belonging to the same geographic area, improving their social experience and fostering discussion and collaboration.
Here are the list of the locations and memories of the 2023 local meet-ups
It was amazing to witness the LoG community gather world-wide around the conference!
Advisory Board
Bastian Rieck
Principal Investigator, Institute of AI for Health, Helmholtz Munich
Jian Tang
Assistant Professor, HEC Montréal, Mila
Jie Tang
Professor, Tsinghua University
Jure Leskovec
Professor, Stanford University
Marinka Zitnik
Assistant Professor, Harvard University
Michael Bronstein
Professor, University of Oxford
Petar Veličković
Staff Research Scientist, DeepMind
Pietro Liò
Full Professor, University of Cambridge
Razvan Pascanu
Research Scientist, DeepMind
Regina Barzilay
Professor, Massachusetts Institute of Technology (MIT)
Shuiwang Ji
Professor, Texas A&M University
Smita Krishnaswamy
Associate Professor, Yale University
Soledad Villar
Assistant Professor, Johns Hopkins University (JHU)
Stefanie Jegelka
Associate Professor, Massachusetts Institute of Technology (MIT)
Stephan Günnemann
Professor, Technische Universität München (TUM)
Thomas Kipf
Senior Research Scientist, Google Brain
Wei Wang
Professor, University of California, Los Angeles
Xavier Bresson
Associate Professor, National University of Singapore (NUS)
Organizing Committee
Adeesh Kolluru
PhD Student, Carnegie Mellon University
Adrian Arnaiz
PhD Student, ELLIS Alicante
Alex Morehead
PhD Student, University of Missouri
Arjun Subramonian
PhD Student, UCLA
Chaitanya K. Joshi
PhD Student, University of Cambridge
Guadalupe Gonzalez
Senior ML Scientist, Genentech
Haitao Mao
PhD Student, Michigan State University
Hannes Stärk
PhD Student, Massachusetts Institute of Technology (MIT)
Iulia Duta
PhD Student, University of Cambridge
Junhyun Lee
PhD Student, Korea University
Luis Müller
PhD Student, RWTH Aachen University
Mathieu Alain
PhD Student, University College London (UCL)
Michelle Li
PhD Student, Harvard University
Sofia Bourhim
PhD Student, École Nationale Supérieure d’Informatique et d’Analyse des Systèmes (ENSIAS)
Steve Azzolin
PhD Student, University of Trento
Vignesh Ram Somnath
PhD Student, ETH Zurich
Xiaoxin He
PhD Student, National University of Singapore
Xinyu Yuan
PhD Student, Université de Montréal, Mila
Yanbang Wang
PhD Student, Cornell University
Yanqiao Zhu
PhD Student, University of California, Los Angeles
Yu He
PhD Student, Stanford
Yuanqi Du
PhD Student, Cornell University
Yuguang Wang
Associate Professor, Shanghai Jiao Tong University (SJTU)
Sponsors
To cover the costs associated with organizing an in-person and virtual conference, we are looking for corporate sponsors. These include costs for: costs derived from the in-person conference, 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!