Frequency

Every year

Summary

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method.

Content

Keywords

machine learning, neural networks, scientific machine learning

Learning Outcomes

By the end of the course, the student must be able to:

  • orient themselves in scientific problems where tools of machine learning may be applied
  • be able to understand and discuss the related literature
  • identify suitable questions and tools

Resources

Bibliography

Machine Learning and the Physical Sciences, Reviews of Modern Physics, arXiv: 1903.10563

Dans les plans d'études

  • Forme de l'examen: Exposé (session libre)
  • Matière examinée: Lecture series on scientific machine learning
  • Cours: 14 Heure(s)
  • Projet: 28 Heure(s)
  • Forme de l'examen: Exposé (session libre)
  • Matière examinée: Lecture series on scientific machine learning
  • Cours: 14 Heure(s)
  • Projet: 28 Heure(s)
  • Forme de l'examen: Exposé (session libre)
  • Matière examinée: Lecture series on scientific machine learning
  • Cours: 14 Heure(s)
  • Projet: 28 Heure(s)
  • Forme de l'examen: Exposé (session libre)
  • Matière examinée: Lecture series on scientific machine learning
  • Cours: 14 Heure(s)
  • Projet: 28 Heure(s)

Semaine de référence