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


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Learning on Graphs Conference 2023

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
  • November 27th, 2023: Conference Starts (Virtual, free to attend)
  • November 30th, 2023: Conference Ends

Program Chairs

Contact PCs: pcs@logconference.org. Full program committee list.


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Soledad Villar

Assistant Professor, Johns Hopkins University (JHU)

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Benjamin Chamberlain

Staff Machine Learning Researcher, Twitter

Advisory Board


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Regina Barzilay

Professor, Massachusetts Institute of Technology (MIT)

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Xavier Bresson

Associate Professor, National University of Singapore (NUS)

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Michael Bronstein

Professor, University of Oxford & Head of Graph ML, Twitter

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Stephan Günnemann

Professor, Technische Universität München (TUM)

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Stefanie Jegelka

Associate Professor, Massachusetts Institute of Technology (MIT)

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Shuiwang Ji

Professor, Texas A&M University

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Thomas Kipf

Senior Research Scientist, Google Brain

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Jure Leskovec

Associate Professor, Stanford University

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Pietro Liò

Full Professor, University of Cambridge

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Razvan Pascanu

Research Scientist, DeepMind

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Bastian Rieck

Principal Investigator, Institute of AI for Health, Helmholtz Munich

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Jian Tang

Assistant Professor, HEC Montréal, Mila

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Jie Tang

Professor, Tsinghua University

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Petar Veličković

Staff Research Scientist, DeepMind

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Soledad Villar

Assistant Professor, Johns Hopkins University (JHU)

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Marinka Zitnik

Assistant Professor, Harvard University

Organizing Committee


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Yuanqi Du

PhD Student, Cornell University

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Hannes Stärk

PhD Student, Massachusetts Institute of Technology (MIT)

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Chaitanya K. Joshi

PhD Student, University of Cambridge

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Andreea Deac

PhD Student, Université de Montréal, Mila

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Iulia Duta

PhD Student, University of Cambridge

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Joshua Robinson

PhD Student, Massachusetts Institute of Technology (MIT)

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Yanqiao Zhu

PhD Student, University of California, Los Angeles

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Kexin Huang

PhD Student, Stanford University

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Michelle Li

PhD Student, Harvard University

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Sofia Bourhim

PhD Student, École Nationale Supérieure d’Informatique et d’Analyse des Systèmes (ENSIAS)

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Ilia Igashov

PhD Student, École Polytechnique Fédérale de Lausanne (EPFL)

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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!

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