EIC Software: AI WG Meeting

Name: EIC Software: AI WG Meeting
Start: 2022-06-22T09:00:00-04:00
End: 2022-06-22T11:05:00-04:00
Location: No location set

Wednesday 22 Jun 2022, 09:00 → 11:05 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