Call for Papers

The workshop features two external contributions tracks:

  1. Paper submission
  2. Scientific model submission

In the call for papers, we invite scientists from diverse backgrounds to submit their work combining scientific and machine learning models as 4-pages papers. All accepted contributions will be presented at a physical poster session, or a 10 minutes video for virtual attendees. In addition, four outstanding contributions selected from the call for papers and the call for models will be presented as 15 minutes contributed talks and recognised by an award funded by the workshops sponsors.

The workshop invites submissions on (but not limited to) the following topics:

  • Real-world application of the combination of scientific and ML modelling: How can scientific models capitalise on ML to exploit raw data to broaden their applicability in the real world?
    • Astronomy
    • Biology
    • Chemistry
    • Geology
    • Robotics
    • Sub-domains of engineering
    • etc.
  • Methodological and theoretical study on the combination of scientific and ML modelling: How can ML take advantage of the large amounts of data and human efforts hidden behind scientific models?
    • Model class and neural architectures
    • Learning algorithms
    • Data preparation
    • Theoretical analysis

Criteria for a successful paper submission include: novelty, correctness, relevance to the field, at the intersection of ML and sciences, and showing promise for future impact. Negative or null results that add value and insight are welcome.

Awards & contributed talks

Awards shall be attributed to the four most oustanding contributions selected from the call for papers and the call for models with the financial supports of the workshop sponsors. Authors of the recognised contributions will have the opportunity to present their work as 15 minutes-long contributed talks.

Posters

Accepted work shall preferably be presented as posters during the workshop. However, in order to facilitate viewing presentations in different time zones, the authors of each accepted paper will get the opportunity to submit a 10 minute video that summarizes their work. Authors of submitted papers will be able to indicate their preference for an in-person presentation or a virtual presentation. Instructions to upload videos will follow.

Key dates

  • Submission Deadline: May 24, 2023, 23:59 AoE   May 29, 2023, 23:59 AoE (extended)
  • Review Deadline: June 7, 2023, 23:59 AoE   June 12, 2023, 23:59 AoE (extended)
  • Decision: June 16, 2023   by June 19, 2023 (extended)
  • Camera-ready: July 21, 2023, 23:59 AoE   (Camera-Ready Instruction)
  • Workshop: July 28, 2023

Authors instructions

Format

  • Submissions should be short papers (extended abstracts) up to 4 pages in PDF format, typeset using the paper template of the workshop (adapted from the ICML template).
  • We adopt the double-blind reviewing process, so submissions must be anonymized.
  • The authors are required to include a short statement (approximately one paragraph) about the potential broader impact of their work, including any ethical aspects and future societal consequences, which may be positive or negative. The broader impact statement should come after the main paper content. The impact statement and references do not count towards the page limit.
  • The ICML style template includes a paper checklist intended to encourage best practices for responsible machine learning research (see associated guidelines). We advise authors to follow those best practices when possible.
  • Appendices are highly discouraged, and reviewers will not be required to read beyond the first 4 pages and the impact statement.
  • Workshop organizers retain the right to reject submissions for editorial reasons: for example, any paper surpassing the page limitation or not including the broader impact statement will be desk-rejected.
  • Submissions will be kept confidential until they are accepted and until authors confirm that they can be included in the workshop. If a submission is not accepted, or withdrawn for any reason, it will be kept confidential and not made public.

Submission platform

Submissions to the Paper Track should be uploaded on OpenReview.

Double submission policy

All accepted works will be made available on the workshop website. This does not constitute an archival publication or formal proceedings; authors retain full copyright of their work and are free to publish their extended work in another journal or conference. We allow submission of works that overlap with papers that are under review or have been recently published in a conference or a journal, including physical science journals. However, we do not accept cross-submissions of the same content to multiple workshops at ICML 2023.

Reviewers instructions

Submissions that follow the submission instructions correctly (i.e., are not rejected due to editorial reasons, such as exceeding the page limit, missing the impact statement, etc,) are sent for peer-review. Below are some of the key points about this process that are shared with the reviewers and authors alike. Authors are expected to consider these in preparation of their submissions and when deciding to apply for the reviewer role.

  • Papers are 4 pages long. Appendices are accepted but highly discouraged; the reviewers will not be required to read the appendices.
  • There will be multiple reviewers for each submission.
  • Reviewers will be able to state their confidence in their review.
  • We will provide an easy-to-follow template for reviews so that both the pros and the cons of the submission can be highlighted.
  • Reviewers are expected to have an up-to-date openreview profil as the paper matching will rely on the openreview matching algorithm.
  • Potential conflicts of interest based on institution and author collaboration are addressed through the openreview review system.
  • Criteria for a successful paper submission include: novelty, correctness, relevance to the field, at the intersection of ML and sciences, and showing promise for future impact. Negative or null results that add value and insight are welcome.
  • There will be no rebuttal period. Minor flaws will not be the sole reason for rejection. Incomplete works at an advanced progress stage are welcome.