AIOP Sep. 30, 2024

From epsciwiki
Revision as of 18:01, 30 September 2024 by Tbritton (talk | contribs) (→‎Minutes)
Jump to navigation Jump to search

The current weekly meeting time is every other Monday at 13:00 US/Eastern

Connection Info:

You can connect using ZOOM Video conferencing (ID: 160 515 9491). (Click "Expand" to the right for details -->):

One tap mobile: US: +16692545252,,1602484178# or +16468287666,,1602484178#

Meeting URL: https://jlab-org.zoomgov.com/j/1605159491?pwd=ZnB0Vkp0SCtYZmRPWG1hRGVnQVprUT09&from=addon
Meeting ID: 160 515 9491
Passcode: 680042

Join by Telephone
For higher quality, dial a number based on your current location.
Dial: +1 669 254 5252 US (San Jose)
+1 646 828 7666 US (New York)
+1 646 964 1167 US (US Spanish Line)
+1 551 285 1373 US (New Jersey)
+1 669 216 1590 US (San Jose)
+1 415 449 4000 US (US Spanish Line)
833 568 8864 US Toll-free
Meeting ID: 160 515 9491
International numbers
Join from an H.323/SIP room system
H.323: 161.199.138.10 (US West)
161.199.136.10 (US East)
Meeting ID: 160 515 9491
Passcode: 680042

SIP: 1605159491@sip.zoomgov.com
Passcode: 680042

One tap mobile: US: +16692545252,,1601987443# or +16468287666,,1601987443#

Meeting URL: https://jlab-org.zoomgov.com/j/1605159491?pwd=ZnB0Vkp0SCtYZmRPWG1hRGVnQVprUT09&from=addon
Meeting ID: 160 515 9491
Passcode: 680042

AIOP - Polarized Target

Agenda:

  1. Previous Meeting
  2. Announcements
  3. Conferences/Workshops
  4. Project Progress
  5. PIER Activities
  6. AOT



Minutes

  • AIOP target 9-30
  • Attendees: Thomas, Malachi, Patrick, Armen, David, Torri
  • Talks
    • Patrick should post his slides
    • Torri is half done with the AIOP CHEP talk
  • Progress
    • Torri
      • Reviewed lack of and odd correlation plots
      • Split by Anneal (dosing)
        • Showed a dose vs index plot
        • Irregular number of indices in each data file
        • Same baseline for many runs
        • Showed own fits with a third order (background)
        • Nothing jumping out
        • Suggested looking at baseline sub
    • Armen
      • A trip down memory lane
      • No version control
      • Copy paste galore!
      • Moved from scikit/jupyter to JLab core and BoTorch
      • Showed a really good model that fits true values well
        • Found a bug in model loading preventing newer models from being used
      • Continuing migration to JLab Core
      • Can look at outliers
      • David + Thomas want to see prediction vs true by time


Action Items