Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with...

In this work, we propose a spatially-resolved and wavelength-dependent DSP-based monitoring scheme to accurately estimate the spectral gain profile of C+L-band in-line Erbium-doped fiber amplifiers deployed in a 280-km single mode fiber link.

We present a digital signal processing (DSP) scheme that performs hyperparameter tuning (HT) via Bayesian optimization (BO) to autonomously optimize memory tap distribution of Volterra series and adapt parameters used in the synthetization of a...

While such Explainable AI (XAI) techniques have reached significant popularity for classifiers, so far little attention has been devoted to XAI for regression models (XAIR). In this review, we clarify the fundamental conceptual differences of XAI...

Communication constraints prevent the wide-spread adoption of Federated Learning systems. In this work, we investigate Federated Distillation (FD) from the perspective of communication efficiency by analyzing the effects of active...

In this joint work with the University of Heidelberg, German Cancer Research Center, University Hospital of Erlangen we showed that multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with...

Federated learning suffers in the case of "non-iid" local datasets, i.e., when the distributions of the clients’ data are heterogeneous. One promising approach to this challenge is the recently proposed method FedAUX, an augmentation of federated...

Nearly all diseases are caused by different combinations of exposures. We present the Causes of Outcome Learning approach (CoOL), which seeks to discover combinations of exposures that lead to an increased risk of a specific outcome in parts of...

Recently, the field of explainable AI (XAI) has developed methods that provide such explanations for already trained neural networks. So far XAI methods along with their heatmaps were mainly validated qualitatively via human-based assessment, or...

This research improves deep learning models based on explanations and expertise. The way is to set the annotation matrix for each training sample. Three image classification tasks in forestry verify the method.

We demonstrate a wireless link at 300 GHz using a fiber-coupled PIN photodiode as the transmitter. We achieved a maximum line rate of 160 Gbit/s with 32QAM modulation. The highest spectral efficiency was achieved with 64QAM at 8 GBaud, i.e. 48...

Auditing AI systems is a complex endeavour since multiple aspects have to be considered along the AI lifecycle that require multi-disciplinary approaches. AI audit methods and tools are in many cases subject of research and not practically...