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LoG 2023 : Learning on Graphs Conference

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Link: https://logconference.org/
 
When Nov 27, 2023 - Nov 30, 2023
Where Virtual
Abstract Registration Due Aug 11, 2023
Submission Deadline Aug 21, 2023
Notification Due Nov 13, 2023
Final Version Due Nov 20, 2023
Categories    graph neural networks   geometric deep learning   geometry processing   graph signal processing
 

Call For Papers

*Call For Papers*

We welcome papers from areas broadly related to learning on graphs and geometry. The LoG conference has a proceedings track with papers published in Proceedings for Machine Learning Research (PMLR) and a non-archival extended abstract track. Papers can be submitted through OpenReview using our LaTeX style files (download or Overleaf template). Papers are reviewed double-blind, and reviews are rated for their quality by authors and area chairs. The top reviewers receive high monetary rewards, as described below.

*Important Dates*

(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)

Upcoming deadline: Abstract Submission Deadline (both Tracks): 78d 0h 16m 32s to go!

*Proceedings Track*

Accepted proceedings papers will be published in the Proceedings for Machine Learning Research (PMLR) and are eligible for our proceedings spotlights. Full proceedings papers can have up to 9 pages with unlimited pages for references and appendix.

Submitted papers cannot be already published or under review in any other archival venue. Upon acceptance of a paper, at least one of the authors must join the conference, or their paper will not be included in the proceedings.

*Extended Abstract Track*

Extended abstracts can be up to 4 pages with unlimited pages for references and appendix. The top papers are chosen for our abstract spotlights. Authors of accepted extended abstracts (non-archival submissions) retain full copyright of their work, and acceptance to LoG does not preclude publication of the same material at another venue. Also, submissions that are under review or have been recently published are allowed for submission. Authors must ensure that they are not violating any other venue dual submission policies.

What qualifies as an extended abstract? Extended abstracts need to provide novel insights or enable future research with novel insights. This can be through presenting new ideas/ways of thinking, leading to insightful discussion and feedback, or dissemination of new valuable resources. We also welcome “non-traditional research artifacts” as submissions to the extended abstract track, such as papers highlighting novel datasets, insightful negative results, exciting preliminary results that warrant rapid dissemination, or reproducibility studies.

*Subject Areas*

The following is a summary of LoG’s focus, which is not exhaustive. If you doubt that your paper fits the venue, feel free to contact pcs@logconference.org or logconference@googlegroups.com!

Expressive Graph Neural Networks
GNN architectures (transformers, new positional encodings, …)
Equivariant architectures
Statistical theory on graphs
Causal inference (structural causal models, …)
Algorithmic reasoning
Geometry processing
Robustness and adversarial attacks on graphs
Combinatorial Optimization and Graph Algorithms
Graph Kernels
Graph Signal Processing/Spectral Methods
Graph Generative Models
Scalable Graph Learning Models and Methods
Graphs for Recommender Systems
Graph/Geometric ML for Computer Vision
Knowledge Graphs
Graph ML for Natural Language Processing
Graph/Geometric ML for Molecules (molecules, proteins, drug discovery, …)
Graph ML for Security
Graph ML for Health
Graph/Geometric ML for Physical sciences
Graph ML Platforms and Systems
Self-supervised learning on graphs
Trustworthy graph ML (fairness, privacy, …)
Graph/Geometric ML Infrastructures (datasets, benchmarks, libraries, …)

*Reviewer Rewards*

Area chairs rate the quality of each review in terms of “constructivism.” The 20 highest-rated reviewers will receive an expected reward of $1500 funded by our generous sponsors. The exact number of reviewers that receive an award and the award amount is subject to change and might increase if more sponsor money is leftover than expected. The top reviewer (who is willing to do so) is invited to hold a talk about reviewing at the conference.
If you wish to become a reviewer and are qualified (e.g., by having published graph or geometry papers), you can sign up via this form.

*Review Process*

Submissions will be double-blind: reviewers cannot see author names when conducting reviews, and authors cannot see reviewer names. We use OpenReview to host papers and allow for public discussions that can be seen by all; comments that are posted by reviewers will remain anonymous. However, program chairs can know the reviewers’ identities and reviewers with particularly low-quality reviews can be excluded from future review processes (the review was flagged as low-quality and discussed by multiple area chairs and program chairs).

1. Submissions are uploaded on OpenReview, publicly available, and official reviews are anonymous. Anybody can post comments that are publicly visible, or restrict visibility to e.g. reviewers or area chairs. We also recommend using Anonymous GitHub for authors to anonymize GitHub repositories.
2. Authors can participate in the discussion about their paper at any time.
3. Full reviews are posted by October 20th, when the paper revision period starts. In the 2-week paper revision period, authors are allowed to adjust their paper again.
4. After November 3rd, there will be an internal discussion period amongst reviewers and ACs with the aim of summarising the review process, after which acceptance decisions are made.
5. Accepted papers will be deanonymized (rejected ones can opt-out) after the notification on Nov 24th.

*Preprint Policy*

The existence of non-anonymous preprints (on arXiv or other online repositories, personal websites, social media) will not result in rejection. Authors may submit anonymized work to LoG that is already available as a preprint (e.g., on arXiv) without citing it.

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