Focus on:  Hide Contributions
Europe/Berlin English Login

Machine Learning: practical application to Astrophysics

→ Europe/Berlin
VC (AIP)

VC

AIP

An der Sternwarte 16 14482 Potsdam
Gal Matijevic
Description

2-day Machine Learning workshop

with focus on practical application of diverse
methods to problems in modern astronomy.

=============================

Costs will be shared by the participants.

=============================

Survey-Results

SurveyResults.pdf
Organiser
  • Wednesday, 16 September
    • 09:00 → 10:30
      Introduction to Machine Learning tbd (VC)

      tbd

      VC

      will be published

      •Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks

    • 10:30 → 10:45
      Coffee Break 15m VC

      VC

      AIP

      An der Sternwarte 16 14482 Potsdam
    • 10:45 → 12:15
      Introduction to Machine Learning: Unsupervised Learning tbd (VC)

      tbd

      VC

      to be published

      •Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks

    • 12:15 → 13:15
      Lunch Break 1h VC

      VC

      AIP

      An der Sternwarte 16 14482 Potsdam
    • 13:15 → 15:00
      Introduction to Machine Learning: Supervised learning I tbd (VC)

      tbd

      VC

      tbd

      •Introduction: different types of machine learning algorithms, theoretical background, practical aspects, structure and elements of (convolutional) neural networks

  • Thursday, 17 September
    • 09:00 → 10:30
      very deep neural networks: Supervised learning II tbd (VC)

      tbd

      VC

      use of generative adversarial networks (GANs) for generation of images of galaxies with constraints - semi-supervised case (example: We want computer to generate an image of a certain type of galaxy. The image is close to indistinguishable from an observed image)

    • 10:30 → 11:00
      Coffee Break 30m tbc (VC)

      tbc

      VC
    • 11:00 → 12:30
      Supervised Learning III: generative adversarial networks VC

      VC

      AIP

      An der Sternwarte 16 14482 Potsdam

      use of generative adversarial networks (GANs)

    • 12:30 → 13:30
      Lunch Break 1h VC

      VC

      AIP

      An der Sternwarte 16 14482 Potsdam
    • 13:30 → 15:00
      very deep neural networks: generative adversarial networks tbc (VC)

      tbc

      VC

      use of generative adversarial networks (GANs) for generation of images of galaxies with constraints - semi-supervised case (example: We want computer to generate an image of a certain type of galaxy. The image is close to indistinguishable from an observed image)

Powered by Indico