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Hammers & Nails 2023 - Swiss Edition

29 October 2023 to 3 November 2023
Congressi Stefano Franscini (CSF)
Europe/Zurich timezone

Session

Invited speakers

30 Oct 2023, 09:30
Congressi Stefano Franscini (CSF)

Congressi Stefano Franscini (CSF)

Monte Verità, Ascona, Switzerland

Presentation materials

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  1. 1. Highlights of machine learning in particle physics for computer scientists
    Loukas Gouskos (CERN)
    30/10/2023, 09:30
  2. 2. Interdisciplinary Machine Learning for Fundamental Physics
    Mariel Pettee (Lawrence Berkeley National Lab. (US))
    30/10/2023, 11:00
  3. 6. Geometric Algebra Transformers: A Universal Architecture of Geometric Data
    Taco Cohen
    30/10/2023, 14:00
  4. 7. AI & material science
    Kostya Novoselov
    31/10/2023, 09:00
  5. 8. Machine learning: bridging scale gap between the worlds of materials and particles
    Andrey Ustyuzhanin
    31/10/2023, 10:30
  6. 5. Reduction and Closure of Dynamical Systems using Deep Learning
    Qianxiao Li
    31/10/2023, 11:15
  7. 14. The Vision of End-to-End ML models in HEP
    Lukas Alexander Heinrich (Technische Universitat Munchen (DE))
    01/11/2023, 10:30
  8. 58. Toward Building Large HEP Models with Self-Supervised Learning
    Michael Kagan (SLAC National Accelerator Laboratory (US))
    01/11/2023, 11:20
  9. 25. Simulation-based inference and the places it takes us
    Jakob Macke
    01/11/2023, 13:15
  10. 16. Generative Models - The Key to Manipulating Implicit Distribution for Bayesian Inference
    Francois Lanusse
    01/11/2023, 14:30
  11. 26. Strong Lensing Data Analysis in the Era of Large Sky Surveys
    Laurence Levasseur
    01/11/2023, 16:15
  12. 10. Image Denoising - Not What You Think
    Michael Elad
    01/11/2023, 17:30
  13. 13. Machine learning for the LHC Simulation Chain
    Ramon Winterhalder (UC Louvain)
    02/11/2023, 09:00
  14. 34. Bigger data, shorter time: Real-time inference on specialised hardware for scientific discovery
    Thea Aarrestad (ETH Zurich (CH)), Thea Aarrestad
    02/11/2023, 10:45
  15. 4. Aspects of Deep Learning in Particle Flow
    Eilam Gross, Etienne Dreyer (Weizmann Institute of Science (IL))
    02/11/2023, 12:00
  16. 69. Learning Image Representations Without Manual Annotations and Related Applications
    Piotr Bojanowski
    02/11/2023, 14:00
  17. 70. Calibrated uncertainty quantification in simulator-based inference
    Ann Lee (Carnegie Mellon University)
    02/11/2023, 15:45
  18. 71. Foundation models for science
    Shirley Ho
    02/11/2023, 17:00
  19. 17. Open problems in generative models
    Barnabas Poczos
    03/11/2023, 09:00
  20. 18. Normalizing flows, diffusion and annealing importance sampling
    Alexander Matthews
    03/11/2023, 10:45
  21. 3. Learning Image Representations Without Manual Annotations and Related Applications
    Piotr Bojanowski
  22. 68. Learning Image Representations Without Manual Annotations and Related Applications
    Piotr Bojanowski
  23. 12. Strong Lensing Data Analysis in the Era of Large Sky Surveys
    Laurence Levasseur
  24. 11. TBC
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