Difference between revisions of "AI tutorials"
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* 13:30 Setting up a model and training it (Anupam Siwakoti/Zach Baldwin - 1h15) | * 13:30 Setting up a model and training it (Anupam Siwakoti/Zach Baldwin - 1h15) | ||
* 14:45 Final performance evaluation (Zach Baldwin - 1h15) | * 14:45 Final performance evaluation (Zach Baldwin - 1h15) | ||
| − | * 16:00 Break ( | + | * 16:00 Break (30min) |
* 16:30 AI: Data Quality Monitoring (Thomas Britton - 30min) | * 16:30 AI: Data Quality Monitoring (Thomas Britton - 30min) | ||
Revision as of 09:33, 18 February 2025
Contents
Purpose
The overall topic is: „Best practice for AI in nuclear physics applications“. We wish to cover the following items via plenary talks and/or interactive tutorials:
- Feature engineering --> Feature normalization, correlation coefficients, feature selection, etc.
- Overfitting --> Dropout layers, weight regularization, etc.
- Performance evaluation --> ROC-Curve, confusion matrix, accuracy, loss curves,...
- Visualization --> How to properly present the performance of a model ? What are "good" diagnostic plots ?
- Data fed into models --> What data sets are used ? Numerical, vs. Images, raw data vs. clean data,...
- Optional, depending on time: HPO --> Tune the parameters of your model
- Optional, depending on time: Different network architectures
Location and Time
The workshop will take place at:
DATES: February 18 (all day) - 19 (morning only), 2025
LOCATION: CEBAF Center F113
Remote Participation
Zoom link can be found below:
References
Workshop Software
- Google online jupyther notebook: https://colab.google/
Install jupyter on your linux machine
install-jupyter-notebook-in-windows
Daniel's example:
Agenda
AI Tutorials
Feb 18
- 09:00 Welcome (5min)
- 09:05 Brief introduction to Machine and Deep Learning (Daniel Lersch - 1h35)
- 10:40 Break (20 min)
- 11:00 Notebook setup (15min)
- 11:15 Data preparation and feature engineering (Anupam Siwakoti - 1h15)
- 12:30 Lunch (1 h)
- 13:30 Setting up a model and training it (Anupam Siwakoti/Zach Baldwin - 1h15)
- 14:45 Final performance evaluation (Zach Baldwin - 1h15)
- 16:00 Break (30min)
- 16:30 AI: Data Quality Monitoring (Thomas Britton - 30min)
Feb 19
- 09:30 A TMVA example (Andrew Schick - 1h)
- 10:30 Break (20min)
- 10:50 Graph Neural Network (Ahmed Mohammed - 30min)
Registration
Please add your name to the list of attendees below. No formal registration or registration fee is required.
| Name | Home Institution | Level | Participate at JLab | |
|---|---|---|---|---|
| ig | JLab | Staff | Yes | |
| Daniel | JLab | Staff | Yes | |
| Gyang | Virginia Tech | Student | No | |
| Karthik | William and Mary | Postdoc | No | |
| Zachary Baldwin | Carnegie Mellon University | Graduate Student | Yes | |
| Nizar Septian | Florida State University | Student | Yes | |
| Alex Austregesilo | JLab | Staff | Yes | |
| Drew Smith | JLab | Postdoc | Yes | |
| Sean Dobbs | FSU | Faculty | Yes | |
| Will Imoehl | Carnegie Mellon University | Postdoc | No | |
| Farah Afzal | Ruhr University Bochum | Faculty | Yes | |
| Peter Hurck | Glasgow | Faculty | Yes | |
| Lawrence Ng | JLab | Postdoc | Yes | |
| Albert Fabrizi | University of Mass. Amherst | Graduate Student | Yes | |
| Shannen Graham-Howard | University of Mass. Amherst | Graduate Student | Yes | |
| Jiawei Guo | Carnegie Mellon University | Graduate Student | Yes | |
| Boris Grube | JLab | Staff | Yes | |
| Churamani Paudel | FIU | Postdoc | No | |
| Vitor Shen | Ruhr University Bochum | Graduate Student | No | |
| Kevin Saldaña | Indiana University | Graduate Student | Yes |
