Deep representation learning for domain adaptable classification of infrared spectral imaging data. - Arne P. Raulf; Joshua Butke; Claus Küpper; Frederik Großerüschkamp; Klaus Gerwert; Axel Mosig (Bioinform., 2020)

Deep Neural Networks for the Correction of Mie Scattering in Fourier-Transformed Infrared Spectra of Biological Samples. - Arne P. Raulf; Joshua Butke; Lukas Menzen; Claus Küpper; Frederik Großerüschkamp; Klaus Gerwert; Axel Mosig (CoRR, 2020)

SmoothLRP: Smoothing LRP by Averaging over Stochastic Input Variations. - Arne P. Raulf; Sina Däubener; Ben Hack; Axel Mosig; Asja Fischer (ESANN, 2021)

Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection. - Patrick Feifel; Benedikt Franke; Arne P. Raulf; Friedhelm Schwenker; Frank Bonarens; Frank Köster (AISafety@IJCAI, 2022)

Potential analysis of a Quantum RL controller in the context of autonomous driving. - M. Lautaro Hickmann; Arne P. Raulf; Frank Köster; Friedhelm Schwenker; Hans-Martin Rieser (ESANN, 2023)

Requirements for Explainability and Acceptance of Artificial Intelligence in Collaborative Work. - Sabine Theis; Sophie F. Jentzsch; Fotini Deligiannaki; Charles Berro; Arne Peter Raulf; Carmen Bruder (HCI (40), 2023)

Tensor networks for quantum machine learning. - Hans-Martin Rieser; Frank Köster; Arne Peter Raulf (CoRR, 2023)

Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation. - Markus Gross; Arne P. Raulf; Christoph Räth (CoRR, 2023)

Robustness and Regularization in Hierarchical Re-Basin. - Benedikt Franke; Florian Heinrich; Markus Lange; Arne P. Raulf (ESANN, 2024)

On Advancements of the Forward-Forward Algorithm. - Mauricio Ortiz Torres; Markus Lange; Arne P. Raulf (CoRR, 2025)