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Learning to Discover : Advanced Pattern Recognition

14–25 Oct 2019
Institut Pascal, Orsay. Paris
Europe/Zurich timezone

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Contribution List

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  1. 1. Introduction: Goals & Modes
    Andreas Salzburger (CERN)
    14/10/2019, 09:30
  2. 2. Institut Pascal: Welcome and Mission Statement from the director
    Denis Ullmo (LPTMS)
    14/10/2019, 09:50
  3. 3. Practicalities
    Sabrina Soccard (Institut Pascal)
    14/10/2019, 10:10
  4. 4. Pattern Recognition in HEP
    Markus Elsing (CERN)
    14/10/2019, 11:00

    Review and outlook on track reconstruction & pattern recognition in high energy physics

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  5. 5. Path operators for thin objects restoration
    Prof. Talbot Hugues (CentraleSupélec, Université Paris-Saclay)
    14/10/2019, 14:00

    In this talk we will present path operators, which are efficient recursive mathematical morphology connected operators that use paths as structuring elements. These operators are designed to preserve thin objects in images, such as hair, cilia, vessels, oriented textures, etc, which are traditionally very difficult to filter using classical operators in many settings. By combining these...

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  6. 48. Announcement
    Andreas Salzburger (CERN)
    15/10/2019, 09:20
  7. 6. Summary of the TrackML Challenge
    Moritz Kiehn (Universite de Geneve (CH))
    15/10/2019, 09:30
  8. 7. Q&A, Discussion
    15/10/2019, 10:30
  9. 8. Track reconstruction with similarity hashing
    Sabrina Amrouche (Université de Geneve (CH))
    15/10/2019, 11:30
  10. 9. Q&A, Discussion
    15/10/2019, 12:30
  11. 10. Graph networks for track reconstruction
    Marcel Kunze (Heidelberg University)
    15/10/2019, 14:00
  12. 11. Q&A, Discussion
    15/10/2019, 15:00
  13. 12. GPU usage in HEP
    Felice Pantaleo (CERN)
    16/10/2019, 09:30
  14. 13. Q&A, Discussion
    16/10/2019, 10:30
  15. 14. Variable latency tracking at 30 MHz
    Vladimir Gligorov (Centre National de la Recherche Scientifique (FR))
    16/10/2019, 11:30
  16. 15. Q&A, Discussion
    16/10/2019, 12:30
  17. 16. Performance vs Portability vs Productivity vs Precision : a trail in the hardware and software jungle.
    David Chamont (LAL)
    16/10/2019, 14:00
  18. 17. Q&A, Discussion
    16/10/2019, 15:00
  19. 18. Quantum Computing meets HEP
    Lucy Linder
    17/10/2019, 09:30
  20. 19. Q&A, Discussion
    17/10/2019, 10:30
  21. 49. Introduction to random matrices and tensors, and application to Principal Component Analysis)
    17/10/2019, 11:30
  22. 20. Optical random features for large-scale machine learning
    Laurent Daudet
    17/10/2019, 14:00
  23. 21. Demo of OPU on ML applications
    Iacopo Poli
    17/10/2019, 14:45
  24. 51. OPU Hands-On
    17/10/2019, 16:00
  25. 22. Event Displays in HEP
    Edward Moyse (University of Massachusetts (US))
    18/10/2019, 09:30
  26. 23. Q&A, Discussion
    18/10/2019, 10:30
  27. 24. VR and AR in HEP
    Tobias Isenberg (Inria)
    18/10/2019, 11:30
  28. 25. Q&A, Discussion
    18/10/2019, 12:30
  29. 53. Phoenix Hands-on
    Emilio Cortina
    18/10/2019, 14:00
  30. 50. Institut Pascal - an introduction
    Jacques Bittoun
    21/10/2019, 09:30
  31. 26. HEP.TrkX, Exa.TrkX & beyond
    Jean-Roch Vlimant (California Institute of Technology (US))
    21/10/2019, 09:45
  32. 27. Q&A, Discussion
    21/10/2019, 10:45
  33. 28. Scattering transform for pattern recognition
    Edouard Oyallon (Centre de Vision Numérique)
    21/10/2019, 11:30
  34. 29. Q&A, Discussion
    21/10/2019, 12:30
  35. 30. ACTS Status & plans
    Andreas Salzburger (CERN)
    21/10/2019, 14:00
  36. 31. Q&A, Discussion
    21/10/2019, 15:00
  37. 52. ACTS hands-on
    Andreas Salzburger (CERN)
    21/10/2019, 16:00
  38. 32. The Mikado algorithm & beyond
    Sergey Gorbunov (Johann-Wolfgang-Goethe Univ. (DE))
    22/10/2019, 09:30
  39. 33. Q&A, Discussion
    22/10/2019, 10:30
  40. 34. Timing detectors in Phase-2
    Corentin Allaire (Centre National de la Recherche Scientifique (FR))
    22/10/2019, 11:15
  41. 35. Timing in propagation and pattern recognition
    Fabian Klimpel (Max-Planck-Institut fur Physik (DE))
    22/10/2019, 11:45
  42. 36. Q&A, Discussion
    22/10/2019, 12:15
  43. 41. Running Data Challenges
    David Rousseau (LAL-Orsay, FR)
    23/10/2019, 09:30
  44. 42. Q&A, Discussion
    23/10/2019, 10:30
  45. 43. N-Body simulations and beyond
    Kazuya Koyama (University of Portsmouth)
    23/10/2019, 10:45
  46. 44. Q&A, Discussion
    23/10/2019, 11:30
  47. 45. Metric learning
    Prof. Amaury Habrard (Université Saint-Étienne)
    23/10/2019, 12:00
  48. 46. Q&A, Discussion
    23/10/2019, 13:00
  49. 47. Deep learning for cosmology
    Anais Moller, Moeller Anais
    23/10/2019, 14:15
  50. 54. Q&A, Discussion
    23/10/2019, 15:15
  51. 37. Fast indexing based on the latent space representation
    Slava Voloshynovskiy (Université de Genève)
    24/10/2019, 10:30
  52. 38. Q&A, Discussion
    24/10/2019, 11:30
  53. 39. Graph networks for vertex reconstruction
    Jonathan Shlomi (Weizmann Institute of Science (IL))
    24/10/2019, 13:30
  54. 40. Q&A, Discussion
    24/10/2019, 14:30
  55. 55. Attempted Summary
    Andreas Salzburger (CERN)
    25/10/2019, 09:30