Deep Learning for Physical Sciences

This website was used for the 2017 instance of this workshop.
Please visit ml4physicalsciences.github.io for up-to-date information.

About

Physical sciences span problems and challenges at all scales in the universe: from finding exoplanets and asteroids in trillions of sky-survey pixels, to automatic tracking of extreme weather phenomena in climate datasets, to detecting anomalies in event streams from the Large Hadron Collider at CERN. Tackling a number of associated data-intensive tasks, including, but not limited to, regression, classification, clustering, dimensionality reduction, likelihood-free inference, generative models, and experimental design are critical for furthering scientific discovery. The Deep Learning for Physical Sciences (DLPS) workshop invites researchers to contribute papers that demonstrate progress in the application of machine and deep learning techniques to real-world problems in physical sciences (including the fields and subfields of astronomy, chemistry, Earth science, and physics).

We will discuss research questions, practical implementation challenges, performance / scaling, and unique aspects of processing and analyzing scientific datasets. The target audience comprises members of the machine learning community who are interested in scientific applications and researchers in the physical sciences. By bringing together these two communities, we expect to strengthen dialogue, introduce exciting new open problems to the wider NeurIPS community, and stimulate production of new approaches to solving science problems. Invited talks from leading individuals from both communities will cover the state-of-the-art techniques and set the stage for this workshop.

NeurIPS 2017

The Deep Learning for Physical Sciences (DLPS) 2017 workshop will be held on December 8, 2017 as a part of the 31st Annual Conference on Neural Information Processing Systems, at the Long Beach Convention & Entertainment Center, Long Beach, CA, United States. Please check the main conference website for information about registration, schedule, venue, and travel arrangements.

Photos from 2017 workshop

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Schedule

Accepted papers

Call for papers

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

• Application of machine and deep learning to physical sciences
• Generative models
• Likelihood-free inference
• Variational inference
• Simulation-based models
• 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 papers will be made available on the workshop website and presented as posters or contributed talks during the workshop. As this does not constitute an archival publication or formal proceedings, authors are free to publish their extended work elsewhere. 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.

Up to 6 accepted submissions will be selected for 20-minute contributed talks.

Submission instructions

Submissions should be anonymized short papers up to 4 pages in PDF format, typeset using the NeurIPS style. References do not count towards the page limit. Appendices are discouraged, and any appendix pages will be included in the 4-page limit. A workshop-specific modified NeurIPS style file will be provided for the camera-ready versions, after the author notification date.

Submissions are handled through the EasyChair website for DLPS 2017. Please note that at least one coauthor of each accepted paper will be expected to attend the workshop in person to present a poster or give a contributed talk.

Submit paper

Travel support and complimentary registration

We have a number of complimentary workshop registrations that will be handed out to paper authors. We also have travel support available particularly for students and junior researchers, thanks to the generous support from our sponsors.

To apply for complimentary registration and travel support, please submit your paper and get in touch with the contact address listed at the bottom of this page, briefly describing your circumstances (e.g., undergraduate or graduate student, postdoctoral researcher, junior faculty, etc.) and intended travel plans (travel origin).

Important dates

• Submission deadline: November 1, 2017 November 3, 2017, 23:59 PDT
• Author notification: November 10, 2017 November 13, 2017
• NeurIPS deadline to cancel registration: November 16, 2017
• Camera-ready (final) paper deadline: December 1, 2017
• Workshop: December 8, 2017

Information for Accepted Papers and Posters

Please produce a "camera-ready" (final) version of your accepted paper by replacing the "nips_2017.sty" style file with the "nips_dlps_2017.sty" file available here and using the "final" option (that is, "\usepackage[final]{nips_dlps_2017}") to include author and affiliation information. The modified style file replaces the first page footer to refer to the workshop instead of the main conference. It is acceptable if your paper goes above the 4-page limit (excluding references) due to author and affiliation information appearing. It is not acceptable to make revisions beyond minor corrections and to include material that was not present in the reviewed version of your paper.

Please upload the final PDF as an updated version in your existing submission on EasyChair. The uploaded final version will be hosted in the workshop website in an "accepted papers" section.

For your posters, we suggest A0 size measuring 841 × 1189 mm (33.1 × 46.8 in). Note that the workshop venue cannot accommodate posters larger than 910 × 1220 mm (36 × 48 in). All accepted papers that do not have an oral presentation (contributed talks in the schedule) are expected to be presented as posters. Posters are optional for oral presenters.

Organizers

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  Ruth Angus
  Columbia University

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  Atılım Güneş Baydin
  University of Oxford

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  Kyle Cranmer
  New York University

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  Daniela Huppenkothen
  New York University

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  Michela Paganini
  Yale University

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  Prabhat
  NERSC, Berkeley Lab

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  Savannah Thais
  Yale University

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  Frank Wood
  University of Oxford

Sponsors

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  Cray Inc.

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  Gordon and Betty
  Moore Foundation

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  Intel Nervana

Location

Promenade Room 104C, Long Beach Convention & Entertainment Center, 300 E Ocean Blvd, Long Beach, CA 90802, United States