08.128.614 Convolutional Neural Networks and Deep Learning in Physics

Course offering details

Instructors: Univ.-Prof. Dr. Matthias Schott

Event type: Lecture

Displayed in timetable as: Neural Networks

Hours per week: 2

Credits: 3,0

Language of instruction: Englisch

Min. | Max. participants: - | -

Requirements / organisational issues:
Basic knowledge in Python

Contents:
In the lecture we will learn about the basic concepts of convolutional neural networks as well as deep learning approaches. We will use those for various applications in physics, starting from high energy physics analysis over data-taking towards solving the Schrödinger Equation.

Recommended reading list:
- Einführung in Machine Learning mit Python: Praxiswissen Data Science Taschenbuch – 26. Juni 2017

Appointments
Date From To Room Instructors
1 Mon, 15. Apr. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
2 Mon, 29. Apr. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
3 Mon, 6. May 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
4 Mon, 13. May 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
5 Mon, 20. May 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
6 Mon, 27. May 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
7 Mon, 3. Jun. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
8 Mon, 17. Jun. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
9 Mon, 24. Jun. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
10 Mon, 1. Jul. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
11 Mon, 8. Jul. 2019 08:00 10:00 Univ.-Prof. Dr. Matthias Schott
Course specific exams
Description Date Instructors Mandatory
1. Written Examination Tue, 16. Jul. 2019 16:00-17:30 Univ.-Prof. Dr. Matthias Schott No
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Instructors
Univ.-Prof. Dr. Matthias Schott