40 citations · 45 across the 5 of their papers we have counts for
5 papers
Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection
Patrick Feifel, Benedikt Franke, Frank Bonarens +3
Reliable pedestrian detection represents a crucial step towards automated driving systems. However, the current performance benchmarks exhibit weaknesses. The currently applied met…
Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation
Markus Gross, Arne P. Raulf, Christoph Räth
We investigate the stationary (late-time) training regime of single- and two-layer underparameterized linear neural networks within the continuum limit of stochastic gradient desce…
Requirements for Explainability and Acceptance of Artificial Intelligence in Collaborative Work
Sabine Theis, Sophie Jentzsch, Fotini Deligiannaki +3
The increasing prevalence of Artificial Intelligence (AI) in safety-critical contexts such as air-traffic control leads to systems that are practical and efficient, and to some ext…
Tensor networks for quantum machine learning
Hans-Martin Rieser, Frank Köster, Arne Peter Raulf
Once developed for quantum theory, tensor networks have been established as a successful machine learning paradigm. Now, they have been ported back to the quantum realm in the emer…
Deep Neural Networks for the Correction of Mie Scattering in Fourier-Transformed Infrared Spectra of Biological Samples
Arne P. Raulf, Joshua Butke, Lukas Menzen +4
Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of (resonant) Mie scattering, which often overshadows biochemical…