Machine Learning and the Physical Sciences

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  Official NeurIPS ML4PS schedule
  (for NeurIPS attendees)

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  ML4PS Gather Town
  (for NeurIPS attendees)

Schedule

Papers/Posters

Organizers

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  Atılım Güneş Baydin
  University of Oxford

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  Juan Felipe Carrasquilla
  Vector Institute / University of Waterloo

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  Adji Bousso Dieng
  Columbia University

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  Karthik Kashinath
  NERSC, Berkeley Lab

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  Gilles Louppe
  University of Liège

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  Brian Nord
  Fermilab

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  Michela Paganini
  Facebook AI Research

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  Savannah Thais
  Princeton University / IRIS-HEP

Steering Committee

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  Anima Anandkumar
  Caltech / NVIDIA

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  Kyle Cranmer
  New York University

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  Shirley Ho
  Flatiron / Princeton / Carnegie Mellon

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  Prabhat
  NERSC, Berkeley Lab

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  Lenka Zdeborova
  Institut de Physique Théorique

Call for papers

We invite researchers to submit work particularly in the following and related areas:

• Application of machine learning to physical sciences
• Generative models
• Likelihood-free inference
• Variational inference
• Simulation-based inference
• Implicit models
• Probabilistic models
• Model interpretability
• Approximate Bayesian computation
• Strategies for incorporating prior scientific knowledge into machine learning algorithms
• Experimental design
• Any other area related to the subject of the workshop

Submissions of completed projects as well as high-quality works in progress are welcome. All accepted short papers (extended abstracts) 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 extended abstracts that overlap with papers that are under review or have been recently published in a conference or a journal. However, we do not accept cross submissions of the same extended abstract to multiple workshops at NeurIPS. Submissions will be kept confidential until they are accepted and 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.

Accepted work will be presented as posters during the workshop. Please note that at least one coauthor of each accepted paper will be expected to have a NeurIPS conference registration that includes the workshop session and participate in one of the virtual poster sessions.

Submission instructions

Submissions should be anonymized short papers (extended abstracts) up to 4 pages in PDF format, typeset using the NeurIPS style. The authors are required to include a short statement (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 (see the NeurIPS style files for an example). The impact statement and references do not count towards the page limit. Appendices are discouraged, and reviewers are not expected to read beyond the first 4 pages and the impact statement. A workshop-specific modified NeurIPS style file will be provided for the camera-ready versions, after the author notification date.

Submissions page is here.

Submit paper

Instructions for Accepted Papers

Camera-ready papers

Please produce a "camera-ready" (final) version of your accepted paper by replacing the "neurips_2020.sty" style file with the "neurips_2020_ml4ps.sty" file available here and using the "final" package option (that is, "\usepackage[final]{neurips_2020_ml4ps}") to include author and affiliation information. The modified style file replaces the first page footer to correctly refer to the workshop instead of the main conference. It is acceptable if your paper goes up to five pages (excluding the broader impact statement, acknowledgments, references, and any appendices) due to author and affiliation information taking extra space on the first page. The five-page limit is strict, and appendices are allowed but discouraged.

Please revise your paper as much as you can to reasonably address reviewer comments. The revision would include minor corrections and/or changes to directly address reviewer comments. Beyond these points, it is not acceptable to include any significant new material that was not present in the reviewed version of your paper.

Please upload the final PDF of your paper by the camera-ready deadline, by logging in to the submission website and using the camera-ready link shown with your submission.

Posters and optional videos

The poster sessions will take place virtually in several GatherTown sessions. Posters will be presented during live and interactive sessions with virtual poster boards, whereby the presenter and the participants will interact with audio and video. You will have control of your audio and video and can turn them on and off at any point as you wish. GatherTown emulates a physical poster session venue where attendees can freely walk from poster to poster and interact in groups with the presenters through audio/video. Posters will be visible in full within the GatherTown platform and the attendees will have the possibility to zoom in to parts of your poster.

Optionally, you can produce a 5-minute video in addition to your poster, upload it to YouTube and provide the YouTube URL for us to share in GatherTown. The video would be a brief presentation of your work described in the paper and the poster.

Posters and optional videos will also be shared on the website of the workshop.

• Please prepare an A0 landscape poster PDF. The landscape orientation ensures that your poster is seen best in computer screens. We have observed a regular A0 format works well in the GatherTown interface.
• Submit your poster together with your optional video using the Google form here
• The poster deadline is set to December 4, 2020, 23:59 PDT.

Important dates

• Submission deadline: September 25, October 2, October 5, 2020, 23:59 PDT
• Author notification: October 23, October 30, 2020
• Camera-ready (final) paper deadline: November 23, November 30, 2020, 23:59 PDT
• Poster deadline: December 4, 2020, 23:59 PDT
• Workshop: December 11, 2020

Registration

NeurIPS conference has three main sessions (Tutorials, Conference, Workshops) to which you can register. You need to be registered to at least the Workshop session in order to be able to attend this workshop. For the latest registration-related information please refer to NeurIPS 2020 website.

About

Machine learning methods have had great success in learning complex representations of data that enable novel modeling and data processing approaches in many scientific disciplines. Physical sciences span problems and challenges at all scales in the universe: from finding exoplanets in trillions of sky pixels, to developing solutions to the quantum many-body problem and combinatorial problems, to detecting anomalies in event streams from the Large Hadron Collider, to predicting how extreme weather events will vary with climate change. Tackling a number of associated data-intensive tasks including, but not limited to, segmentation, computer vision, sequence modeling, causal reasoning, generative modeling, and probabilistic inference are critical for furthering scientific discovery in these and many other areas. In addition to using machine learning models for scientific discovery, the ability to interpret what a model has learned is receiving an increasing amount of attention.

In this targeted workshop, we aim to bring together computer scientists, mathematicians and physical scientists who are interested in applying machine learning to various outstanding physical problems including in inverse problems, approximating physical processes, understanding what a learned model represents, and connecting tools and insights from the physical sciences to the study of machine learning models. In particular, the workshop invites researchers to contribute short papers (extended abstracts) that demonstrate cutting-edge progress in the application of machine learning techniques to real-world problems in the physical sciences and/or using physical insights to understand and improve machine learning techniques.

By bringing together machine learning researchers and physical scientists who apply machine learning, we expect to strengthen the interdisciplinary dialogue, introduce exciting new open problems to the broader community, and stimulate the production of new approaches to solving challenging open problems in the sciences. Invited talks from leading individuals in both communities will cover the state-of-the-art techniques and set the stage for this workshop.

NeurIPS 2020

The Machine Learning and the Physical Sciences 2020 workshop will be held on December 11, 2020 as a part of the 34th Annual Conference on Neural Information Processing Systems. Originally planned to be at the Vancouver Convention Centre, Vancouver, BC, Canada, NeurIPS 2020 and this workshop will take place entirely virtually (online). Please check the main conference website for the latest information.

Sponsors

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Location

Originally planned to be at the Vancouver Convention Centre, Vancouver, BC, Canada, NeurIPS 2020 and this workshop will take place entirely virtually (online). Please check the main conference website for the latest information.