Name: Machine Learning for Fundamental Physics School 2024
Start: 2024-08-12T00:00:00-07:00
End: 2024-08-16T17:15:00-07:00
Location: No location set

Machine Learning for Fundamental Physics School 2024

from Monday, 12 August 2024 (00:00) to Friday, 16 August 2024 (17:15)

Monday, 12 August 2024
08:30 Welcome Presentation - Sascha Diefenbacher (LBL) Elham E Khoda (University of California, San Diego) Aishik Ghosh (UCI) Benjamin Nachman (LBL)
Welcome Presentation
- Sascha Diefenbacher (LBL)
- Elham E Khoda (University of California, San Diego)
- Aishik Ghosh (UCI)
- Benjamin Nachman (LBL)
08:30 - 09:00
Room: Auditorium
09:00 Introduction to Machine Learning: Part I - Joshua Bloom (University of California, Berkeley)
Introduction to Machine Learning: Part I
- Joshua Bloom (University of California, Berkeley)
09:00 - 10:30
10:30 Coffee Break
Coffee Break
10:30 - 11:00
11:00 Tutorial: Intro to Neural Networks I - Oz Amram (Fermilab) Johannes Wagner (University of California, Berkeley) Jay Chan (LBNL)
Tutorial: Intro to Neural Networks I
- Oz Amram (Fermilab)
- Johannes Wagner (University of California, Berkeley)
- Jay Chan (LBNL)
11:00 - 12:00
Tutorial Instruction for environment setup: https://docs.google.com/presentation/d/1fwWOHHByf_nWvCfTVi1rCbVAmkaOHEN_IUTC1HoVvM0/edit?usp=sharing Git repo: https://github.com/ml4fp/2024-lbnl/tree/main
12:00 Lunch
Lunch
12:00 - 13:30
13:30 Tutorial: Intro to Neural Networks II - Jay Chan (University of Wisconsin-Madison) Johannes Wagner (University of California, Berkeley)
Tutorial: Intro to Neural Networks II
- Jay Chan (University of Wisconsin-Madison)
- Johannes Wagner (University of California, Berkeley)
13:30 - 14:00
14:00 Introduction to Machine Learning: Part II - Dennis Noll (Lawrence Berkeley National Lab. (US))
Introduction to Machine Learning: Part II
- Dennis Noll (Lawrence Berkeley National Lab. (US))
14:00 - 15:30
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00 Tutorial: ML tools for HEP data - Johannes Wagner (University of California, Berkeley) Jay Chan (University of Wisconsin-Madison)
Tutorial: ML tools for HEP data
- Johannes Wagner (University of California, Berkeley)
- Jay Chan (University of Wisconsin-Madison)
16:00 - 18:00
Tuesday, 13 August 2024
09:00 Application: Transformers I - Alex Shmakov (UCI)
Application: Transformers I
- Alex Shmakov (UCI)
09:00 - 10:00
Room: Auditorium
10:00 Coffee Break
Coffee Break
10:00 - 10:30
10:30 Application: Transformers II - Alex Shmakov (UCI)
Application: Transformers II
- Alex Shmakov (UCI)
10:30 - 12:00
12:00 Lunch
Lunch
12:00 - 13:30
13:30 Overview of ML in particle physics - Benjamin Nachman
Overview of ML in particle physics
- Benjamin Nachman
13:30 - 14:30
14:30 Break
Break
14:30 - 14:45
14:45 Applications: Generative Models I - Sascha Diefenbacher (Lawrence Berkeley National Laboratory)
Applications: Generative Models I
- Sascha Diefenbacher (Lawrence Berkeley National Laboratory)
14:45 - 15:45
15:45 Coffee Break
Coffee Break
15:45 - 16:15
16:15 Application: Generative Models II - Sascha Diefenbacher (Lawrence Berkeley National Laboratory)
Application: Generative Models II
- Sascha Diefenbacher (Lawrence Berkeley National Laboratory)
16:15 - 17:30
Wednesday, 14 August 2024
09:00 Uncertainties - Aishik Ghosh
Uncertainties
- Aishik Ghosh
09:00 - 10:00
Room: Auditorium
10:00 Coffee Break
Coffee Break
10:00 - 10:15
10:15 Differentiable Programming - Sean Gasiorowski (SLAC)
Differentiable Programming
- Sean Gasiorowski (SLAC)
10:15 - 12:30
12:30 Lunch
Lunch
12:30 - 14:00
14:00 Unfolding - Vinicius Mikuni
Unfolding
- Vinicius Mikuni
14:00 - 15:30
15:30 Coffee Break
Coffee Break
15:30 - 16:00
16:00 Industry Talk - Kanishka Rao (Google)
Industry Talk
- Kanishka Rao (Google)
16:00 - 17:00
17:00 Networking Event
Networking Event
17:00 - 18:00

18:30 Dinner
Dinner
18:30 - 20:30
Thursday, 15 August 2024
09:00 Anomaly Detection - Oz Amram (Fermilab)
Anomaly Detection
- Oz Amram (Fermilab)
09:00 - 10:30
Room: Auditorium
10:30 Coffee Break
Coffee Break
10:30 - 11:00
11:00 Optimal Transport - Nathan Suri (Yale University)
Optimal Transport
- Nathan Suri (Yale University)
11:00 - 12:30
12:30 Lunch
Lunch
12:30 - 14:00
14:00 ML at Scale - Steven Farrell (NERSC/LBL)
ML at Scale
- Steven Farrell (NERSC/LBL)
14:00 - 15:00
15:00 Break
Break
15:00 - 15:15
15:15 Efficient ML I - Elham E Khoda (University of California, San Diego)
Efficient ML I
- Elham E Khoda (University of California, San Diego)
15:15 - 16:15
16:15 Coffee Break
Coffee Break
16:15 - 16:30
16:30 Efficient ML II - Elham E Khoda (University of California, San Diego)
Efficient ML II
- Elham E Khoda (University of California, San Diego)
16:30 - 17:30
17:30 Closeout: General Session - Maris Arthurs (SLAC/Stanford) Sascha Diefenbacher (Lawrence Berkeley National Laboratory) Benjamin Nachman Oz Amram (Fermilab) Steven Farrell Aishik Ghosh Elham E Khoda (University of California, San Diego)
Closeout: General Session
- Maris Arthurs (SLAC/Stanford)
- Sascha Diefenbacher (Lawrence Berkeley National Laboratory)
- Benjamin Nachman
- Oz Amram (Fermilab)
- Steven Farrell
- Aishik Ghosh
- Elham E Khoda (University of California, San Diego)
17:30 - 17:50
Friday, 16 August 2024
09:00 ATLAS
ATLAS
09:00 - 17:15
Room: Auditorium
Contributions

09:00 Overview of ML in ATLAS - Daniel Murnane

10:30 Neural Simulation-based Inference (NSBI) I - Aishik Ghosh Andrew Skivington (UCI)

13:30 Neural Simulation-based Inference (NSBI) II - Aishik Ghosh Andrew Skivington (UCI)

14:30 ATLAS b-tagging Framework: SALT - Johannes Wagner (University of California, Berkeley)

16:15 Athena deployment with ONNX - Sascha Diefenbacher (Lawrence Berkeley National Laboratory)

17:00 Closeout & Final Remarks - Aishik Ghosh Benjamin Nachman Maris Arthurs (SLAC/Stanford) Oz Amram (Fermilab) Sascha Diefenbacher (Lawrence Berkeley National Laboratory) Steven Farrell
CMS
CMS
09:00 - 17:15
Room: 66-3-316
Contributions

09:00 CMS Specific Session
LZ
LZ
09:00 - 17:15
Room: 62-2-203
Contributions

09:00 LZ Specific Session

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