9–12 Apr 2018
CERN
Europe/Zurich timezone
There is a live webcast for this event.

Identifying the relevant dependencies of the neural network response on characteristics of the input space

10 Apr 2018, 16:55
20m
500/1-001 - Main Auditorium (CERN)

500/1-001 - Main Auditorium

CERN

400
Show room on map

Speaker

Stefan Wunsch (KIT - Karlsruhe Institute of Technology (DE))

Description

The use of neural networks in physics analyses poses new challenges for the estimation of systematic uncertainties. Since the key to a proper estimation of uncertainties is the precise understanding of the algorithm, novel methods for the detailed study of the trained neural network are valuable.
This talk presents an approach to identify those characteristics of the neural network inputs that are most relevant for the response and therefore provides essential information to determine the systematic uncertainties.

Intended contribution length 20 minutes

Primary authors

Stefan Wunsch (KIT - Karlsruhe Institute of Technology (DE)) Raphael Marius Friese (KIT - Karlsruhe Institute of Technology (DE)) Roger Wolf (KIT - Karlsruhe Institute of Technology (DE)) Gunter Quast (KIT - Karlsruhe Institute of Technology (DE))

Presentation materials