Arne Peter Raulf

• Dr. rer. nat.
• Head of Department at German Aerospace Center (DLR)

We investigate the stationary (late-time) training regime of single- and two-layer underparameterized linear neural networks within the continuum limit of stochastic gradient descent (SGD) for synthetic Gaussian data. In the case of a single-layer network in the weakly underparameterized regime, the spectrum of the noise covariance matrix deviates...

We investigate the stationary (late-time) training regime of single-and two-layer linear neural networks within the continuum limit of stochastic gradient descent (SGD) for synthetic Gaussian data. In the case of a single-layer network in the weakly oversampled regime, the spectrum of the noise covariance matrix deviates notably from the Hessian, w...

Once developed for quantum theory, tensor networks (TNs) have been established as a successful machine learning (ML) paradigm. Now, they have been ported back to the quantum realm in the emerging field of quantum ML to assess problems that classical computers are unable to solve efficiently. Their nature at the interface between physics and ML make...

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 extent explainable to humans to be trusted and accepted. The present structured literature analysis examines \(n = 236\) articles on the requirements for the explainability...

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 extent explainable to humans to be trusted and accepted. The present structured literature analysis examines n = 236 articles on the requirements for the explainability and...

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 extent explainable to humans to be trusted and accepted. The present structured literature analysis examines n = 236 articles on the requirements for the explainability and a...

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 emerging field of quantum machine learning to assess problems that classical computers are unable to solve efficiently. Their nature at the interface between physics and mach...

The reliable DNN-based perception of pedestrians represents a crucial step towards automated driving systems. Currently applied metrics for a subset-based evaluation prohibit an application-oriented performance evaluation of DNNs for pedestrian detection. We argue that the current limitation in evaluation can be mitigated by the use of image segmen...

Polyp bailout is a drastic response to acute stress where coral coloniality breaks down and polyps detach. We induced polyp bailout in Pocillopora acuta with heat stress and tested for differential gene expression using RNAseq and a qPCR assay. Furthermore, we induced polyp bailout with hypersalinity and compared the results to identify stressor-in...

Introduction In a retrospective analysis of two randomized phase III trials in mCRC patients treated first line with oxaliplatin, fluoropyrimidine with and without Bevacizumab (the AIO KRK 0207 and R091 trials) we evaluated the association of high microsatellite instability (MSI-H), immunoscore (IS) and PD-L1 expression in relation to overall survi...

Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of scattering effects, often Mie scattering, which probably overshadows biochemically relevant spectral information by a non‐linear, non‐additive spectral component in Fourier transform infrared (FTIR) spectroscopic measurements. Corre...

Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of (resonant) Mie scattering, which often overshadows biochemically relevant spectral information by a non-linear, non-additive spectral component in Fourier transformed infrared (FTIR) spectroscopic measurements. Correspondingly, many...

Motivation: Applying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which are non-linear in nature and lead to classifiers that do not generalize well, e.g. across differen...

Motivation: Applying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which are non-linear in nature and lead to classifiers that do not generalize well, e.g. across different...