ICLR 2021 : 9th International Conference on Learning Representations

in Conferences   Posted on July 16, 2020 

Conference Information

Submission Deadline Monday 28 Sep 2020 Proceedings indexed by :
Conference Dates May 4, 2021 - May 8, 2021
Conference Address Vienna, Austria
Conference & Submission Link https://iclr.cc/Conferences/2021/CallForPapers
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 11.38
#Contributing Top Scientists 97
#Papers published by Top Scientists 132
Google Scholar H5-index 203
Guide2Research Overall Ranking: 17
Category Rankings
Machine Learning & Artificial Intelligence 9

Conference Call for Papers

ICLR 2021 – Call For Papers

Vienna, Tue May 4th through Sat the 8th

We invite submissions to the 2021 International Conference on Learning Representations, and welcome paper submissions from all areas of machine learning and deep learning.

Key dates

The planned dates are as follow:

Abstract submission: 28 September 2020, 08:00 AM PDT

Submission date: 2 October 2020, 08:00 AM PDT

Reviews released: 10 November 2020

Author discussion period ends: 24 November 2020

Final decisions: 12 January 2021

Subject Areas

We consider a broad range of subject areas including feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization, as well as applications in vision, speech recognition, text understanding, games, music, computational biology, and others.

A non-exhaustive list of relevant topics:

unsupervised, semi-supervised, and supervised representation learning

representation learning for planning and reinforcement learning

representation learning for computer vision and natural language processing

metric learning and kernel learning

sparse coding and dimensionality expansion

hierarchical models

optimization for representation learning

learning representations of outputs or states

theoretical issues in deep learning

visualization or interpretation of learned representations

implementation issues, parallelization, software platforms, hardware

applications in audio, speech, robotics, neuroscience, computational biology, or any other field

societal considerations of representation learning including fairness, safety, privacy

Double blind reviewing

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. The program will include keynote presentations from invited speakers, oral presentations, and posters.

Authors can revise their paper as many times as needed up to the paper submission deadline. Changes to the paper will not be allowed while the paper is being reviewed. During the discussion phase (between area chairs, reviewers and authors), edits will again be allowed; a pdfdiff will be done against the submission at the paper submission deadline. Area chairs and reviewers reserve the right to ignore changes which are significant from the original scope of the paper. Like in the past two years, Workshops will have their own organisation and call for contributions.

Submission Instructions

This year we are asking authors to submit paper abstracts by the abstract submission deadline of 28 September 2020, 08:00 AM PDT (UTC-7). The full paper submission deadline is 2 October 2020, 08:00 AM PDT (UTC-7). Abstracts and papers must be submitted using the conference submission system at: https://openreview.net/group?id=ICLR.cc/2021/Conference. Abstracts submitted by the abstract submission deadline must be genuine, placeholder or duplicate abstracts will be removed.

Paper length

There will be a strict upper limit of 8 pages for the main text of the initial submission, with unlimited additional pages for citations. Note that the upper page limit differs from last year!

Authors may use as many pages of appendices (after the bibliography) as they wish, but reviewers are not required to read these.

During the rebuttal phase and for the camera ready version, authors are allowed one additional page for the main text, for a strict upper limit of 9 pages.

Style files and Templates

To prepare your submission to ICLR 2021, please use the LaTeX style files provided at:


Authors are strongly encouraged to participate in the public discussion of their paper, as well as of any other paper submitted to the conference. Submissions and reviews are both anonymous. For detailed instructions about the format of the paper, please visit www.iclr.cc.

Reviewing Process

Submissions to ICLR are uploaded on OpenReview, which enables public discussion. Official reviews are anonymous and publicly visible. Anybody who is logged in can post comments that are publicly visible or restrict visibility to reviewers and up, ACs and up, or just PCs. In addition, the author of a comment can decide to post anonymously or not. Login is required before posting any comment.

Authors are encouraged to revise their paper as many times as needed up until the paper submission deadline. Authors can participate in the discussion about their paper, as well as about any other paper submitted to the conference, at any time.

By 4 November 2019, reviewers need to post their full review. Reviews are anonymous and publicly visible in Open Review. Once the reviews are posted, authors are free to upload modifications to the paper during the two week discussion period.

During the discussion period, authors may address reviewer comments and make changes to their papers. During this period, a pdfdiff will be applied to compare new changes to the paper against the original submission. Area chairs and reviewers reserve the right to ignore changes that are significantly different from the original paper. In addition, during this period, any submission that is cited will be given an anonymous BibTex entry

After discussion 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. Papers that are not accepted will be considered non-archival, and may be submitted elsewhere (modified or not), although the OpenReview site will maintain the reviews, the comments, and links to the versions submitted to ICLR.

Code of Conduct

All ICLR participants, including authors, are required to adhere to the ICLR code of conduct (https://iclr.cc/public/CodeOfConduct). More detailed guidance for authors, reviewers, and all other participants will be made available in due course, and participation will require acknowledging and adhering to the provided guidelines.

Dual Submission Policy

Submissions that are identical (or substantially similar) to versions that have been previously published, or accepted for publication, or that have been submitted in parallel to this or other conferences or journals, are not allowed and violate our dual submission policy. However, papers that cite previous related work by the authors and papers that have appeared on non-peer reviewed websites (like arXiv) or that have been presented at workshops (i.e., venues that do not have publication proceedings) do not violate the policy. The policy is enforced during the whole reviewing process period. Submission of the paper to archival repositories such as arXiv is allowed.

To allow citation of papers that are under review at ICLR2021, OpenReview provides BibTeX entries that do not list the authors, but does give the title, year and url. Author names are revealed at the end of the conference.

Withdrawal Policy

Authors have the right to withdraw papers from consideration at any time until paper notification. Before the paper submission deadline, if an author withdraws the paper it will be deleted from the OpenReview hosting site. However, note that after the paper submission deadline, if an author chooses to withdraw a submission, it will remain hosted by OpenReview in a publicly visible “withdrawn papers” section. Like on arXiv, submissions to ICLR cannot be deleted or modified. Withdrawn papers will be de-anonymized right away.

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