Theorie-Seminare WS 19/20

 

Do. 10.10.2019, 16.30 Uhr

J. Thompson (Uni Heidelberg)

(Machine) Learning to be Unsure

Abstract:
Machine learning methods are becoming ubiquitous in particle physics. However, many of these techniques
suffer from overconfidence and a lack of associated uncertainties. In this talk, I will discuss how Bayesian neural networks can address these problems and help us to understand model uncertainties in a machine learning context. In order to do this, I will first explore how these uncertainties can be understood in a frequentist framework, before considering how the Bayesian neural network responds to statistical and systematic uncertainties.

 

Do. 17.10.2019, 16.30 Uhr

S. Paßehr (RWTH Aachen)

Towards high-precision predictions for Higgs masses and decays in theories beyond the
Standard Model

 

Do. 24.10.2019, 16.30 Uhr

K. Ng (GRAPPA, Amsterdam)

TBA

 

Do. 31.10.2019, 16.30 Uhr

M. Mühlleitner (KIT)

TBA

 

Do. 07.11.2019, 16.30 Uhr

R. Teyssier (Uni Zürich)

TBA

 

Do. 14.11.2019, 16.30 Uhr

L. Magnea (U. Torino)

TBA

 

Do. 21.11.2019, 16.30 Uhr

M. Bustamante (NBI, Copenhagen)

TBA

 

Do. 05.12.2019, 16.30 Uhr

D.J.E. Marsh (Uni Göttingen)

TBA

 

Do. 12.12.2019, 16.30 Uhr

M. Wiesemann (CERN und MPI München)

TBA

 

Do. 09.01.2020, 16.30 Uhr

A. Fialkov (University of Sussex)

TBA

 

Do. 16.01.2020, 16.30 Uhr

M. Diehl (DESY)

TBA

 

Do. 23.01.2020, 16.30 Uhr

A. Font-Ribera (UC London)

TBA

 

Do. 30.01.2020, 16.30 Uhr

C. Sturm (U. Würzburg)

TBA