MINERVA – Machine Learning for Radioastronomy at Observatoire de Paris
MachINe lEarning for Radioastronomy at obserVatoire de PAris
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  • Welcome
  • Team Members
  • SKA DC
  • EoR
  • Transients
  • Ressources
  • Open Positions
    • M1 Internship (Closed)
    • MASTER 2 Internship (closed)
    • Position 1 : David Cornu (2020-2022)
    • Position 2 (Closed) (2022-2024)
  • Seminars
    • Seminar cycle
    • Workshops
  • Methods and Data
    • Machine Learning – Introduction / material
    • Radio-Observatories – A flavour
    • Data Access – Examples
  • Contacts
    • Contact information
    • Mailing List

Learning

Books (on-line)

  • Hastie ElemStatLearn
  • mit-deep-learning-book-pdf
  • NeuralNetworksPosteriors_Lippmann1991.pdf
  • BishopPatternRecognitionAndMachineLearningSpringer2006.pdf
  • MachineLearningProbabilisticPerspective.pdf
  • understanding-machine-learning-theory-algorithms.pdf
  • HandsonMachineLearningwithScikitLearnandTensorflow.pdf
  • a_short_1995.pdf
  • Generative Deep Learning

    More resources

Lecture (Videos)

  • Yann Lecun L’apprentissage profond (2015-2016)
  • Youtube Channel gricad

Tutorials and Slides

  • https://gricad-gitlab.univ-grenoble-alpes.fr/talks/fidle/
  • https://github.com/mhuertascompany/deeplearning4astronomy
  • https://gricad-gitlab.univ-grenoble-alpes.fr/talks/fidle/-/wikis/resources-links?version_id=47fddcee4feab2628d4e8019483350b2db827fcc#

Tensor Flow

  • https://www.tensorflow.org
  • http://playground.tensorflow.org/
  • The MINERVA team is the winner of the second SKA data challenge

    In 2021 July 31st, the MINERVA team won the SKA data challenge 2 with a score of 23 254. Link to the leaderboard with the frozen scores.

  • Previous and upcoming seminars

    On tuesdays (2pm Paris time)
    Workshops and Seminars

  • Seminars on Youtube

    Minerva.Live on Youtube

MINERVA – Machine Learning for Radioastronomy at Observatoire de Paris
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