activity
20112024
most citedThe analytic properties of the quark propagator from an effective infrared interaction model

45 citations · 263 across the 20 of their papers we have counts for

collaborators

23 papers

cond-mat.mtrl-sci2024

Vibrations and damping of the eigenmodes of viscoelastic nanospheres with thermal conductivity

Markus Wenin, Andreas Windisch

In this paper, we derive a series of exact analytical closed expressions to calculate the complex eigenfrequencies and the displacement for the corresponding eigenmodes of a viscoe…

cs.CV2023★ 9 cited

Evaluation of Data Augmentation and Loss Functions in Semantic Image Segmentation for Drilling Tool Wear Detection

Elke Schlager, Andreas Windisch, Lukas Hanna +3

Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example. In this paper, we present a U-Net…

astro-ph.SR2022★ 12 cited

Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data

Hannah T. Rüdisser, Andreas Windisch, Ute V. Amerstorfer +4

Interplanetary coronal mass ejections (ICMEs) are one of the main drivers for space weather disturbances. In the past, different approaches have been used to automatically detect e…

hep-ph2021★ 2 cited

A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations

Andreas Windisch, Thomas Gallien, Christopher Schwarzlmueller

Dyson-Schwinger equations (DSEs) are a non-perturbative way to express n-point functions in quantum field theory. Working in Euclidean space and in Landau gauge, for example, one c…

physics.space-ph2021★ 25 cited

Machine learning for predicting the Bz magnetic field component from upstream in situ observations of solar coronal mass ejections

Martin A. Reiss, Christian Möstl, Rachel L. Bailey +6

Predicting the Bz magnetic field embedded within ICMEs, also known as the Bz problem, is a key challenge in space weather forecasting. We study the hypothesis that upstream in situ…

hep-ph2019★ 7 cited

Deep reinforcement learning for complex evaluation of one-loop diagrams in quantum field theory

Andreas Windisch, Thomas Gallien, Christopher Schwarzlmueller

In this paper we present a novel technique based on deep reinforcement learning that allows for numerical analytic continuation of integrals that are often encountered in one-loop…