SOCR News APS GDS 2024

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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

Program

Logistics

Time Abstract Invited Speaker
3:00PM - 3:30PM W56.00001: On the use of physics in machine learning for imaging and quantifying complex processes George Barbastathis
3:36PM - 4:12PM W56.00002: Energy Frontier Exploration using Particle Physics and AI Mark S Neubauer
4:12PM - 4:48PM W56.00003: Physics and Constrained Optimization Processes Data-driven medical image formation without a priori models Michael Insana
4:48PM - 5:24PM Aurélien Decelle

Speakers, Titles, and Abstracts

  • ... coming up later ...

Resources

  • ... coming up later ...





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