Sandia National Laboratories Annual ML/DL Workshop
Sept 9th – Sept 12th (Virtual, Open to the public)
SCHEDULE
We are pleased to announce that the 2024 workshop will be hosted out of Albuquerque, New Mexico!
September 9-12th
- July 15-18 Hackathon (Day 1 Morning: In-person, Rest: Virtual, Sandians Only)
- September 4-5 Tutorials Session (Virtual, SNL Staff Only)
All prior presentations have been archived!
MIXERS
- September 9th
- Nuclear Museum Mixer (In Person, New Mexico, Open to public)
- California Mixer TBD (In Person, California, Open to the public)
- September 10th Virtual Mixer (Virtual, Open to public)
- …More Coming!
PRESENTERS
Scheduled presenters will submit talks OR upload a public link via our submission form.
PURPOSE
The Sandia Machine Learning and Deep Learning (MLDL) Workshop is an opportunity for researchers and practitioners in these areas to
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Present work across various national laboratories and collaborators in machine learning (ML) and deep learning (DL).
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Network with staff and management at Sandia focused on work in these areas and discuss ideas for potential new work and collaboration,
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Teach and test MLDL methods via tutorials for those interested in getting some hands-on experience with machine learning and deep learning.
ATTENDANCE
The ML/DL Workshop is virtual for all approved for public release (UUR) sessions. The final versions of accepted talks will be pre-recorded videos delivered virtually by a live session organizer, and speakers will participate in live, virtual Q&A sessions following their talks.
PRESENTATIONS NEEDED
We are looking for presenters interested in sharing their work. We are particularly interested in submissions with regard to
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Describing the development of ML and DL methods and software
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Application of ML and DL methods to problems of interest to the national laboratories
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Existing problems at the laboratories for which ML and/or DL could be applied
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Demonstrations of existing ML and DL software packages and hardware developed at the laboratories
Virtual pre-recorded presentation slots are limited to 15-, 20-, or 30-minute time slots with an opportunity for questions afterwards.
Important Dates:
Submission Deadline June 21st, 2024
Final Notifications by July 11th, 2024
For questions and/or comments, please contact us.