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Ish: Inference of the Mass Composition of Cosmic Rays with Energies from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mn>10</mml:mn><mml:mn>18.5</mml:mn></mml:msup></mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mn>20</mml:mn></mml:mrow></mml:msup><mml:mtext> </mml:mtext><mml:mtext> </mml:mtext><mml:mi>eV</mml:mi></mml:mrow></mml:math> Using the Pierre Auger Observatory and Deep Learning

  1. Long Short-Term Memory

    Sepp Hochreiter, Jürgen Schmidhuber

    Maqola199741 iqtibos
    ABI
  2. Deep learning

    Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton

    Sharh maqola201536 iqtibos
    ABI
  3. End to the Cosmic-Ray Spectrum?

    K. Greisen

    Maqola196613 iqtibos
    ABI
  4. The Pierre Auger Cosmic Ray Observatory

    Aab, A., Abreu, P., Aglietta, M. +30

    Maqola201510 iqtibos
    ABI
  5. Hadronic interaction model sibyll 2.3d and extensive air showers

    Felix Riehn, R. Engel, Anatoli Fedynitch +2

    Maqola20205 iqtibos
    ABI
  6. AugerPrime: the Pierre Auger Observatory Upgrade

    Antonella Castellina

    Maqola20194 iqtibos
    ABI
  7. Sarlavhasiz

    Boshqa3 iqtibos
    ABI