EIC Software: AI WG Meeting

Wednesday 22 Jun 2022, 09:00 → 11:05 US/Eastern

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

 

 

1 Introduction

Speakers: Cristiano Fanelli (MIT), Tanja Horn (Cath)

2 Uncertainty aware ML-based models for accelerator studies (Anomaly detection and surrogate model for RL)

Speaker: Kishan Rajput (Jefferson Lab)

Kishan_AI4EIC_WG3.pdf

09:30 Q/A

3 Uncertainty Quantification for Machine Learning Applied to Data Analysis

Speaker: Benjamin Nachman (Lawrence Berkeley National Laboratory)

EICMLUQ_Summer2022.pdf

10:05 Q/A

4 Inverse problems in nuclear tomography

Speaker: Nobuo Sato (Jefferson Lab)

EIC_ AI WG.pdf

10:40 Q/A

5 Final Discussion