Learning on Graphs Conference


LoG is a new annual research conference that covers areas broadly related to machine learning on graphs and geometry, with a special focus on review quality.

9th – 12th December 2022

Virtual, free to attend


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Learning on Graphs Conference

Schedule

The LoG Conference covers research from areas broadly related to machine learning on graphs and geometry. Registration for the virtual conference in December 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!

The tentative schedule is available now. Register to stay updated!

Keynote Speakers


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Marinka Zitnik

Assistant Professor, Harvard University

Graph AI to Enable Precision Medicine

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Soledad Villar

Assistant Professor, Johns Hopkins University (JHU)

Random Graph Models and Graph Neural Networks

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Stephan Günnemann

Professor, Technische Universität München (TUM)

Graph Neural Networks for Molecular Systems

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Taco Cohen

Research Scientist, Principal Engineer, Qualcomm AI Research

Categories and Causality

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Djork-Arné Clevert

Vice President, Machine Learning Research Hub, Worldwide Research, Development and Medical, Pfizer

Graph Representation Learning for Drug Discovery (Sponsor Talk)

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Tommaso Biancalani

Distinguished Scientist and Director, Genentech, AI/ML (Research Biology)

Title TBD (Sponsor Talk)

Program Chairs

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


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Bastian Rieck

Principal Investigator, Institute of AI for Health, Helmholtz Munich

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Razvan Pascanu

Research Scientist, DeepMind

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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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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Derek Lim

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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Gabriele Corso

PhD Student, Massachusetts Institute of Technology (MIT)

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Leonardo Cotta

PhD Student, Purdue University

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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)

Sponsors

Check out open opportunities with our sponsors!

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