Call for Papers

Submission deadline: Friday, 29th May 2020 Monday, 8 June 2020 (23:59 AoE)
(New deadline!)

Author notification: Monday, 22 June 2020

Camera ready deadline: Monday, 6 July 2020 (23:59 AoE)

Workshop: Friday, 17 July 2020
The workshop will be held virtually due to risks and travel restrictions associated with SARS-CoV-2/COVID-19. For more information from ICML, please see the ICML conference website.

You may submit your paper through CMT, by following this link.

We encourage submissions related to graph representation learning and geometric deep learning. We will especially appreciate submissions that connect directly with the topics of the workshop, as well as papers that introduce interdisciplinary applications and benchmarks.

For this workshop, we also encourage applications relevant to mitigating negative effects of COVID-19. Some examples of impactful use cases: drug repurposing, forecasting via GNN-powered epidemiological models, track-and-trace via GNNs, etc. We provide a set of resources here.

We will welcome original research papers of no more than 4 pages, not including references or supplementary materials. We request and recommend that authors rely on the supplementary material only to include minor details (e.g., hyperparameter settings) that do not fit in the 4 pages. Submissions which also qualify for a contributed talk on novel applications or COVID-19 mitigation should be marked accordingly in CMT.

All accepted papers will be presented in the virtual poster session, with three contributed works, three most promising novel applications, as well as three works on COVID-19 mitigation, being selected for an oral presentation.

All submissions must use the ICML template. Submissions should be in .pdf format, and the review process is double-blind—therefore the papers should be appropriately anonymised. Previously published work (or under-review) is acceptable.

Should you have any questions, please reach out to us via email: