output
20162025
most citedGaia Early Data Release 3: The astrometric solution

1.2k citations

26 papers

quant-ph2025★ 2 cited

AutoQML: A Framework for Automated Quantum Machine Learning

Marco Roth, David A. Kreplin, Daniel Basilewitsch +7

Automated Machine Learning (AutoML) has significantly advanced the efficiency of ML-focused software development by automating hyperparameter optimization and pipeline construction…

quant-ph2024★ 3 cited

Quantum Neural Networks in Practice: A Comparative Study with Classical Models from Standard Data Sets to Industrial Images

Daniel Basilewitsch, João F. Bravo, Christian Tutschku +1

We compare the performance of randomized classical and quantum neural networks (NNs) as well as classical and quantum-classical hybrid convolutional neural networks (CNNs) for the…

physics.optics2024★ 2 cited

Optical tools for laser machining along six orders of magnitude

Julian Hellstern, Christoph Tillkorn, Tim Hieronymus +3

We present an overview on the development and characterization of multiscale laser processing optics for versatile material modifications across more than six orders of magnitude.…

physics.optics2024

Selective laser etching of displays: Closing the gap between optical simulations and fabrication

Martin Wimmer, Myriam Kaiser, Jonas Kleiner +3

Simulations and measurements on selective laser etching of display glasses are reported. By means of a holographic 3D beam splitter, ultrashort laser pulses are focused inside the…

physics.optics2024★ 6 cited

Phase retrieval algorithm applied to high-energy ultrafast lasers

Jikai Wang, Abdolnaser Ghazagh, Sonam Smitha Ravi +6

A standardized phase retrieval algorithm is presented and applied to an industry-grade high-energy ultrashort pulsed laser to uncover its spatial phase distribution. We describe in…

cs.SE2023

Operationalizing Assurance Cases for Data Scientists: A Showcase of Concepts and Tooling in the Context of Test Data Quality for Machine Learning

Lisa Jöckel, Michael Kläs, Janek Groß +8

Assurance Cases (ACs) are an established approach in safety engineering to argue quality claims in a structured way. In the context of quality assurance for Machine Learning (ML)-b…