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Artificial intelligence and modern physics: a two-way connection

29 September 2024 to 5 October 2024
Monopoli (BA)
Europe/Rome timezone

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Contribution List

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  1. 1. Welcome and introduction
    30/09/2024, 08:45
  2. 8. Data access and preparation
    Andrea Beschi
    30/09/2024, 09:20
  3. 2. Data access and preparation
    Andrea Beschi
    30/09/2024, 11:20
  4. 19. Hands-on session 1 (data access and preparation)
    30/09/2024, 14:00
  5. 20. Hands-on session 2 (data access and preparation)
    30/09/2024, 16:00
  6. 7. Bayesian statistics
    Christopher J. Moore
    01/10/2024, 09:20
  7. 11. ML elements
    Dr Riccardo Finotello (CEA Paris-Saclay)
    01/10/2024, 11:20
  8. 21. Hands-on session 3 (Bayesian statistics)
    01/10/2024, 14:20
  9. 22. Hands-on session 4 (ML elements)
    01/10/2024, 16:00
  10. 12. ML elements
    Riccardo Finotello (CEA LIST)
    02/10/2024, 09:20
  11. 13. ML tools
    Stefano Giagu (Sapienza Università di Roma and Istituto Nazionale di Fisica Nucleare)
    02/10/2024, 11:20
  12. 23. Hands-on session 5 (ML elements)
    02/10/2024, 14:20
  13. 24. Hands-on session 6 (ML tools)
    02/10/2024, 16:20
  14. 14. ML tools
    Stefano Giagu (Sapienza Università di Roma and Istituto Nazionale di Fisica Nucleare)
    03/10/2024, 09:20
  15. 15. Bayesian statistics
    Christopher J. Moore
    03/10/2024, 11:20
  16. 17. ML applications to biomedical data
    Guido Sanguinetti (SISSA)
    03/10/2024, 14:20
  17. 25. Hackathon session 1
    03/10/2024, 16:20
  18. 10. Social dinner
    03/10/2024, 20:00

    Terrace above the reception building

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  19. 30. Anomaly detection for new physics searches in HEP
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    Identify rare new physics process through an anomaly detection technique based on deep neural network (Graph Neural Network architecture).

    Material for the exercise i.e. datasets and examples have been copied to the leonardo cluster and are available at:
    /leonardo/home/usertrain/a08trb55/anomalyDetection/LHCO

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  20. 29. Classification of Order and Species of Mosquitoes
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    Conventional manual counting methods for the monitoring of mosquito species and populations can hinder the accurate determination of the optimal timing for pest control in the field. In this exercise is required to train a deep learning-based automated image analysis algorithm, for a two-fold task: the classification of different species and order of mosquito, based on a professionally made...

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  21. 34. Dual Intelligence: Tackling Classification and Regression Challenges
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    We propose an hackathon divided into two challenges: in the first one, participants will tackle a regression problem using the well-known 'Asteroid Dataset', where they need to estimate the diameter of various types of asteroids. In the second challenge, participants will face a classification problem aimed at reconstructing the diagnosis of diabetes for different types of patients based on...

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  22. 35. Exploitation of jets features to tag VBF like events in high energy particle physics
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    The goal of the project is to develop a tagger for distinguishing VBF-like signal events from background ones using properties of the two leading jets (tag jets) and eventually the third one. The key idea is to exploit the color flow patterns in signal events, where the QCD activity between jets is greater between each jet and the beam spot with respect to the region between the two tag jets....

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  23. 33. Integrating Spliced and Unspliced Gene Expression Data for Improved Cell Type Annotation in Single-Cell RNA Sequencing
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    Cell type annotation is one of the primary tasks in single-cell RNA sequencing analysis and it is of a significance importance and difficulty in computational biology. This difficulty arises from two primary factors. First, gene expression levels typically exist on a continuum rather than being discrete, making it harder to draw clear boundaries between different cell types. Second, variations...

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  24. 18. STARFINDER - Machine Learning Techniques for Evaluating Globular Cluster’s Stars Membership Probabilities
    04/10/2024, 10:40
    Hackathon project proposal
    Hackathon

    Abstract

    Globular clusters (GCs), spheroidal conglomeration of stars tightly bound together by means of gravitational force, are among the oldest objects that live within our galaxy. A key characteristic of these objects is their high density, significantly greater than the average galactic star density (between $\sim10^4$ to $\sim10^6$ stars within a spheroid of radius up to...

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  25. 16. Hands-on session 7 (ML tools)
    04/10/2024, 11:20
  26. 27. Hackathon session 3
    04/10/2024, 14:20
  27. 28. Hackathon session 4
    04/10/2024, 16:20
  28. 36. Hackathon: final reports
    04/10/2024, 17:30

    Each group should prepare 3 slides:
    1) Problem statement
    2) Chosen architecture and strategy
    3) Results (showing the FOM indicated in the challenge)
    Send us the slides by email at aiphy@unimib.it

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  29. 3. Data access and preparation
    Dr Andrea Beschi (McKinsey)
  30. 4. Data access and preparation
  31. 5. Data access and preparation
  32. 26. Hackathon session 1
  33. 32. Hackathon session 1
  34. 31. Hackathon session 2
  35. 6. Networking event
  36. 9. Social event