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Machine Learning for Fundamental Physics School (ML4FP) 2026

1–5 Jun 2026

Marcus Nanotechnology Building

US/Eastern timezone

Contribution List

1. Welcome

01/06/2026, 08:45
2. Introduction to Machine Learning: Part I

01/06/2026, 09:00
3. Tutorial: Intro to Neural Networks I

01/06/2026, 11:00
4. Introduction to Machine Learning: Part II

01/06/2026, 13:30
5. Tutorial: Intro to Neural Networks II

01/06/2026, 15:30
6. Overview of ML in collider physics

02/06/2026, 09:00
7. Overview of ML in neutrino physics

02/06/2026, 09:45
8. Differentiable Programming

02/06/2026, 11:00
9. Simulation-based Inference: Part I

02/06/2026, 13:30
10. Simulation-based Inference: Part II

02/06/2026, 15:30
11. Generative Models: Part I

03/06/2026, 09:00
12. Generative Models: Part II

03/06/2026, 11:00
13. Anomaly Detection (Lecture & Tutorial)

03/06/2026, 13:30
24. Neutrino Parallel Session (experiment specific)

03/06/2026, 15:30
14. Transformers: Part I

04/06/2026, 09:00
15. Transformers: Part II

04/06/2026, 11:00
16. Application: Muon Collider BIB (Lecture & Tutorial)

04/06/2026, 13:30
17. Career Panel

04/06/2026, 15:30
18. Efficient Machine Learning (Lecture & Tutorial)

05/06/2026, 09:00
19. ATLAS Parallel Session: Part I

05/06/2026, 11:00
20. CMS Parallel Session: Part I

05/06/2026, 11:00
21. ATLAS Parallel Session: Part II

05/06/2026, 13:30
22. CMS Parallel Session: Part II

05/06/2026, 13:30
23. Closeout Session: Recap and Networking

05/06/2026, 15:30