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PCCP Workshop Series : Bayesian Deep Learning for Cosmology and Gravitational waves

4–6 mars 2020
PCCP, APC laboratory, Université de Paris
Fuseau horaire Europe/Paris

Contact

Session

Invited talk

4 mars 2020, 14:30
Pierre-Gilles de Gennes Amphitheater (PCCP, APC laboratory, Université de Paris)

Pierre-Gilles de Gennes Amphitheater

PCCP, APC laboratory, Université de Paris

10 Rue Alice Domon et Léonie Duquet, 75013 Paris

Documents de présentation

Aucun document.

  1. 46. An Introduction to Bayesian Deep Learning
    Frédéric Pennerath (CentraleSupélec)
    04/03/2020 14:30

    Bayesian Deep Learning (BDL) fills an important gap in the current deep neural networks, no matter powerful they are: in figurative terms, one could say BDL gives to AI the introspective ability to assess its own level of ignorance due to a lack of observations.
    In more technical terms, BDL adopts the view of Bayesian statistics by replacing the weights of neural networks by...

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  2. 47. Bayesian analysis and Supernova Photometric Cosmology
    Dr Emille Ishida (LPC-UCA)
    04/03/2020 17:10

    In the end of the 20th century type Ia supernovae provided the first evidence for accelerated cosmic expansion -- completely changing the cosmological model paradigm. Since then, the astronomical community has devote much of its resources to the construction of large scale sky surveys which are expected to achieve first light in the next few years. The upcoming Large Survey of Space and Time...

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  3. 48. TensorFlow Probability
    Brian Patton (Google)
    05/03/2020 14:00
  4. 42. Graphcore: Innovation in Machine Intelligence Hardware & Software
    Alexander Titterton (Graphcore)
    06/03/2020 14:00
  5. 44. Large-scale Machine Learning on LightOn’s Optical Processing Units
    Laurent Daudet (Light On)
    06/03/2020 14:45
  6. 43. Microsoft Azure
    Alexandre Jean (Microsoft)
    06/03/2020 15:15
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