Workshop on Machine Learning for Physics 2019
- Date: May 21, 2019
- Place: Rosensäle, Fürstengraben 27, 07743 Jena
- Organized by: Institute for Theoretical Physics and Institute of Computer Science, FSU Jena
- Workshop Website: https://indico.tpi.uni-jena.de/event/56/
Machine learning is currently taking various scientific disciplines by storm and physics is no exception. This workshop concentrated on applications of machine learning in physics. In his keynote, Karl Mannheim of University of Würzburg sketched this fascinating and growing field. He argued that there is an urgent need to distinguish between correlations and causality. Another focus of this workshop, which was addressed by three talks, was on applications of machine learning in Earth System Sciences.
Here is a collection of the titles of the presentations:
Title of Presentation | Speaker | Affiliation |
---|---|---|
From Correlation to Causality – Machine Learning in Physics and Astronomy | Prof. Dr. Karl Mannheim | University of Würzburg |
GENO: GENeric Optimization for Machine Learning with an Example from Physics | PD Dr. Sören Laue | FSU Jena |
Perspectives for Causal Inference in Earth System Sciences | Dr. Jakob Runge | German Aerospace Center |
Detection and Attribution of Extreme Events in Earth Observation Time Series | Dr. Maha Shadaydeh | FSU Jena |
Deep Learning for Gravitational Wave Data Analysis | Prof. Dr. Bernd Brügmann | FSU Jena |
Sparse + Low Rank Models | Frank Nussbaum and Prof. Dr. Joachim Giesen | FSU Jena |
The Inverse Modelling Toolbox | Prof. Dr. Rainer Heintzmann | FSU Jena |
Understanding the Earth System with Machine Learning | Prof. Dr. Joachim Denzler and Prof. Dr. Markus Reichstein | FSU Jena and MPI Biogeochemistry |