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IPA workshop on Machine Learning for particle physics and astrophysics (IPA-ML)

Mar 20 – 22, 2023
ETH Zurich
Europe/Zurich timezone

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Contribution List

33 / 33
41. Welcome
Prof. Davide Sgalaberna (ETH Zurich)
3/20/23, 10:00 AM
10. Physics and machine learning: an overview
Dr Saul Alonso Monsalve (ETH Zurich)
3/20/23, 10:30 AM
14. Machine learning lecture
Dr Mauro Donega (ETH Zurich)
3/20/23, 1:30 PM
45. Machine learning (BDT) tutorial
Simone Pigazzini (ETH Zurich), Massimiliano Galli
3/20/23, 3:15 PM
15. Deep learning tutorial
Dr Saul Alonso Monsalve (ETH Zurich)
3/20/23, 4:15 PM

In this tutorial, you'll learn how to use deep learning to perform particle identification. We'll cover the basics of neural networks and how to build them using Python and TensorFlow. Participants will train their own neural networks using a dataset of particle tracks, and learn how to evaluate their performance. To participate, you'll need a Google account for [Google...
16. Introduction on neutrino experiments workflow with emphasis on challenges
Prof. Davide Sgalaberna (ETH Zurich)
3/21/23, 9:00 AM
21. Image reconstruction in a 3D plastic scintillator detector using deep learning
Dr Saul Alonso Monsalve (ETH Zurich)
3/21/23, 9:20 AM
17. Neutrino interaction classification and transfer learning
Dr Leigh Whitehead (University of Cambridge)
3/21/23, 9:40 AM
19. Event filtering and mitigation of simulation biases
Dr Marta Babicz (University of Zurich)
3/21/23, 10:00 AM
20. Event reweighting and generative models in neutrino experiments
Dr Cristovao Vilela (CERN)
3/21/23, 10:50 AM
18. Multi-task data reconstruction chain for imaging detectors in neutrino experiments
Prof. Kazuhiro Terao (SLAC)
3/21/23, 11:10 AM
22. Large Scale Structure Cosmology with Artificial Intelligence
Dr Tomasz Kacprzak (ETH Zurich)
3/21/23, 11:30 AM
23. Cosmological constraints from combined probes of large scale structure with deep learning
Arne Thomsen (ETH Zurich)
3/21/23, 11:50 AM
44. Background rejection in Cherenkov Telescopes
Prof. Adrian Biland (ETH Zurich)
3/21/23, 1:20 PM
25. New generative AI models
Luca Biggio (ETH Zurich)
3/21/23, 1:40 PM
26. Geometric Learning/ Physics-informed AI for cosmology
Dr Tilman Troester (ETH Zurich)
3/21/23, 2:00 PM
24. PointNets for galaxy redshift surveys
Sotirios Anagnostidis (ETH Zurich)
3/21/23, 2:20 PM
27. Introduction on LHC experiments workflow with emphasis on challenges
Prof. Annapaola de Cosa (ETH Zurich)
3/21/23, 3:10 PM
30. Object identification and reconstruction
Dr Alessandro Calandri (ETH Zurich)
3/21/23, 3:30 PM
28. Ultrafast ML inference for triggering
Dr Thea Aarrestad (ETH Zurich)
3/21/23, 3:50 PM
29. Machine learning for data quality monitoring
Roberto Seidita
3/21/23, 4:10 PM
34. Probabilistic models in ML for HEP
Davide Valsecchi (ETH Zurich)
3/21/23, 4:30 PM
31. Data-MC matching
Massimiliano Galli
3/22/23, 9:00 AM
32. Analysis techniques
Florian Eble
3/22/23, 9:20 AM
35. Quantum machine learning
Vasilis Belis (ETH Zurich)
3/22/23, 10:00 AM
37. Machine learning applications
Dr Mauro Verzetti (Google)
3/22/23, 10:50 AM
36. Robotics, event-based imaging
Prof. Davide Scaramuzza (ETH Zurich)
3/22/23, 11:30 AM
40. Knowledge distillation
Patrick Odagiu (ETH Zurich)
3/22/23, 12:00 PM
42. Round table
3/22/23, 1:30 PM
43. Closing
Prof. Annapaola de Cosa
3/22/23, 2:45 PM
33. Anomaly detection
Roberto Seidita (ETH Zurich)
39. Encoding/decoding
Doruk Efe Gökmen
38. Normalizing flows
Javad Komijani
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