Difference between revisions of "SOCR News APS GDS 2024"
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==Session Logistics== | ==Session Logistics== | ||
[[Image:APS_March_2024_Meeting_Minneapolis.png|300px|thumbnail|right| [https://march.aps.org/schedule APS March 2024 Meeting] ]] | [[Image:APS_March_2024_Meeting_Minneapolis.png|300px|thumbnail|right| [https://march.aps.org/schedule APS March 2024 Meeting] ]] | ||
| − | * '''Date/Time''': | + | * '''Date/Time''': ''Mar 7 2024 3:00PM'' [https://time.is/CT CT] |
| − | * '''Venue''': [https://march.aps.org/travel Minneapolis Convention Center, Minneapolis, MN, USA]. | + | * '''Venue''': [https://march.aps.org/travel Minneapolis Convention Center, Minneapolis, MN, USA], ''Room 205AB''. |
* '''Registration''': [https://march.aps.org/registration Meeting Registration is required]. | * '''Registration''': [https://march.aps.org/registration Meeting Registration is required]. | ||
* '''Conference''': [https://march.aps.org/about March 2024 APS Annual Conference]. | * '''Conference''': [https://march.aps.org/about March 2024 APS Annual Conference]. | ||
* [https://march.aps.org/attendees-presenters/abstracts '''Abstract Submission'''] | * [https://march.aps.org/attendees-presenters/abstracts '''Abstract Submission'''] | ||
| − | * '''Session | + | * '''Session''': Invited presentations - [https://meetings.aps.org/Meeting/MAR24/Session/W56 Session W56 Model-based Statistical Physics, Computable Data, and Model-Free Artificial Intelligence] |
| − | * | + | * [https://meetings.aps.org/Meeting/MAR24/ChairIndex APS March 2024 Invited Sessions] |
== Abstract Submission== | == Abstract Submission== | ||
Revision as of 14:50, 22 December 2023
Contents
SOCR News & Events: March 2024 APS Meeting: Model-based Statistical Physics, Computable Data, and Model-Free Artificial Intelligence
Overview
- There are significant recent advances linking model-based statistical inference, quantum physics, computable data science, and model-free artificial intelligence (AI). Interlacing research from these areas has significant potential to lead to novel techniques for understanding and interpreting the physical world. Statistical physics methods model the behavior and interactions of large systems of objects and are applicable far beyond elementary particles. Computational data science algorithms facilitate the pre- and post-processing and analysis of heterogeneous types of information, including structured and unstructured, static and longitudinal, high- and low-dimensional, and complete and missing datasets. Model-free machine learning and AI techniques provide complementary approaches for exploratory, hypotheses-generating, data-mining, clustering, and predictive analytics based on few a priori assumptions. This session will bring a diverse pool of experts to discuss the theoretical challenges, empirical evidence, and potential opportunities of combining transdisciplinary methods to create meta ensemble techniques for holistic comprehensive understanding of complex systems.
Invited Special Session Organizer
Session Logistics
- Date/Time: Mar 7 2024 3:00PM CT
- Venue: Minneapolis Convention Center, Minneapolis, MN, USA, Room 205AB.
- Registration: Meeting Registration is required.
- Conference: March 2024 APS Annual Conference.
- Abstract Submission
- Session: Invited presentations - Session W56 Model-based Statistical Physics, Computable Data, and Model-Free Artificial Intelligence
- APS March 2024 Invited Sessions
Abstract Submission
... coming up later ...
Program
... coming up later ...
Speakers, Titles, and Abstracts
- ... coming up later ...
Resources
- ... coming up later ...
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