472 citations
- Friedrich Schiller University JenaDE19 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- ETH ZurichCH7 papers
- Johannes Gutenberg University MainzDE7 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR6 papers
- Jagiellonian UniversityPL6 papers
- KU LeuvenBE6 papers
- Laboratoire de Physique Corpusculaire de CaenFR6 papers
- Leibniz Institute of Photonic TechnologyDE6 papers
- Paul Scherrer InstituteCH6 papers
- Université Grenoble AlpesFR6 papers
- Université Paris-SudFR6 papers
54 papers
From user-understandable to technical process model: a model-driven approach using cuta4bpm
Kathrin Kirchner, Siniša Nešković, Dejan Stojimirović
For business process modeling, we can choose between graph-oriented and block-oriented languages. Block-oriented languages are more structured and therefore better understandable f…
Free-electron laser-based extended wide-field mid-infrared photothermal imaging for biomedical and microplastic analysis
Anooj Thayyil Raveendran, Subham Adak, Artem Shydliukh +8
Wide-field mid-infrared photothermal (MIP) imaging offers rapid labelfree chemical contrast for biomedical and polymer analysis. However, its field of view (FOV) is limited by the…
An Integrated Open Source Software System for the Generation and Analysis of Subject-Specific Blood Flow Simulation Ensembles
Simon Leistikow, Thomas Miro, Adrian Kummerländer +6
Background and Objective: Hemodynamic analysis of blood flow through arteries and veins is critical for diagnosing cardiovascular diseases, such as aneurysms and stenoses, and for…
Semiconductor Bloch equations in Wannier gauge with well-behaved dephasing
Martin Thümmler, Thomas Lettau, Alexander Croy +2
The semiconductor Bloch equations (SBEs) with a dephasing operator for the microscopic polarizations are a well established approach to simulate high-harmonic spectra in solids. We…
Scaling Up Unbiased Search-based Symbolic Regression
Paul Kahlmeyer, Joachim Giesen, Michael Habeck +1
In a regression task, a function is learned from labeled data to predict the labels at new data points. The goal is to achieve small prediction errors. In symbolic regression, the…
Benchmarking for Practice: Few-Shot Time-Series Crop-Type Classification on the EuroCropsML Dataset
Joana Reuss, Jan Macdonald, Simon Becker +4
Accurate crop-type classification from satellite time series is essential for agricultural monitoring. While various machine learning algorithms have been developed to enhance perf…