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    EIC Software: AI WG Meeting

    → US/Eastern
    Description

    This meeting is topic-oriented and focused on uncertainty quantification. 

    We will use Zoom for the remote meeting:  https://jlab-org.zoomgov.com/j/1614875218?pwd=RFRPcGlNM3BaS0pQaDhxS3JURkdJZz09  

    Meeting ID: 1614875218 Password: 925723

    We will use live notes where everyone can edit comments/questions: https://docs.google.com/document/d/1iPNVJUuTjydop450nsHK78VuziISzwB177KaXTNPips/edit

     

     

      • 09:00 → 09:05
        Introduction 5m
        Speakers: Cristiano Fanelli (MIT), Tanja Horn (Cath)
      • 09:05 → 09:30
        Uncertainty aware ML-based models for accelerator studies (Anomaly detection and surrogate model for RL) 25m
        Speaker: Kishan Rajput (Jefferson Lab)
        Kishan_AI4EIC_WG3.pdf
      • 09:30 → 09:40
        Q/A 10m
      • 09:40 → 10:05
        Uncertainty Quantification for Machine Learning Applied to Data Analysis 25m
        Speaker: Benjamin Nachman (Lawrence Berkeley National Laboratory)
        EICMLUQ_Summer2022.pdf
      • 10:05 → 10:15
        Q/A 10m
      • 10:15 → 10:40
        Inverse problems in nuclear tomography 25m
        Speaker: Nobuo Sato (Jefferson Lab)
        EIC_ AI WG.pdf
      • 10:40 → 10:50
        Q/A 10m
      • 10:50 → 11:00
        Final Discussion 10m