Recent publications

June 2022

Multiparametric MRI for characterization of the basal ganglia and the midbrain

Till M. Schneider, Jackie Ma, Patrick Wagner, Nicolas Behl, Armin Michael Nagel, Mark E. Ladd, Sabine Heiland, Martin Bendszus, Sina Straub

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...


June 2022

Differentially Private One-Shot Federated Distillation

Haley Hoech, Karsten Müller, Wojciech Samek, Roman Rischke

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...


June 2022

Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome

Andreas Rieckmann, Wojciech Samek, Sebastian Lapuschkin, Leila Arras, Piotr Dworzynski, Onyebuchi A. Arah, Naja H. Rod, Claus T. Ekstrom

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...


June 2022

A Benchmark Dataset for the Ground Truth Evaluation of Neural Network Explanations

Leila Arras, Wojciech Samek, Ahmed Osman

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...


May 2022

Improve the Deep Learning Models in Forestry Based on Explanations and Expertise

Ximeng Cheng, Ali Doosthosseini, Julian Kunkel

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.


May 2022

Coherent Wireless Link at 300 GHz with 160 Gbit/s Enabled by a Photonic Transmitter

Simon Nellen, Sebastian Lauck, Emilien Peytavit, Pascal Szriftgiser, Martin Schell, Guillaume Ducourn, Björn Globisch

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...


May 2022

Towards Auditable AI Systems: From Principles to Practice

Christian Berghoff, Thomas Wiegand, Wojciech Samek, Markus Wenzel, Jona Böddinghaus, Vasilios Danos, Gabrielle Davelaar, Thomas Doms, Heiko Ehrich, Alexandru Forrai, Radu Grosu, Ronan Hamon, Henrik Junklewitz, Matthias Neu, Simon Romanski, Dirk Schlesinger, Jan-Eve Stavesand, Sebastian Steinbach, Arndt von Twickel, Robert Walter, Johannes Weissenböck

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...


May 2022

Overview of the Neural Network Compression and Representation (NNR) Standard

Heiner Kirchhoffer, Karsten Müller, Werner Bailer, Fabien Racape, Wojciech Samek, Shan Liu, Miska M. Hannuksela, Paul Haase, Hamed Rezazadegan-Tavakoli, Francesco Cricri, Emre Aksu, Wei Jiang, Wei Wang, Swayambhoo Jain, Shahab Hamidi-Rad

Neural Network Coding and Representation (NNR) is the first international standard for efficient compression of neural networks. The NNR standard contains quantization and an arithmetic coding scheme as core encoding and decoding technologies, as...


April 2022

ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

Daniel Becking, Karsten Müller, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer

In this chapter, we develop and describe a novel quantization paradigm for DNNs: Our method leverages concepts of explainable AI (XAI) and concepts of information theory: Instead of assigning weight values based on their distances to the...


April 2022

Explaining the Predictions of Unsupervised Learning Models

Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek, Jacob R. Kauffmann

In this chapter, we review our recently proposed "neuralization-propagation" (NEON) approach for bringing XAI to workhorses of unsupervised learning. NEON first converts the unsupervised model into a functionally equivalent neural network so...


April 2022

xxAI - Beyond Explainable AI

Andreas Holzinger, Klaus-Robert Müller, Wojciech Samek, Randy Goebel, Ruth Fong, Taesup Moon

This book takes next steps towards a broader vision for explainable AI in moving beyond explaining classifiers, to include explaining other kinds of models (e.g., unsupervised and reinforcement learning models) via a diverse array of XAI...



March 2022

Hybrid Polymer THz Receiver PIC with Waveguide Integrated Photoconductive Antenna: Concept and 1st Characterization Results

Tianwen Qian, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David DeFelipe, Moritz Baier, Simon Nellen, Björn Globisch, Hauke Conradi, Milan Deumer, Y Durvasa Gupta, Madeleine Weigel, Jakob Reck, Klara Mihov, Ben Schuler, Martin Kresse

An all-photonic THz-receiver PIC comprising an on-chip frequency stabilization scheme and a novel InP-based photoconductive antenna is presented in this paper. Characterization of the key photonic building blocks shows the functionality of the...


March 2022

Coherent Detection With Double-Side Vertically Illuminated Photodiodes for Spatially Resolved Ranging Applications

Pascal Rustige, Patrick Runge, Martin Schell, Felix Ganzer

We theoretically investigate and demonstrate coherent detection with double-side vertically illuminated photodiodes by injecting signal and local oscillator collinearly from opposite sides of the photodetector chip. A first proof of concept for...


March 2022

A new concept for spatially resolved coherent detection with vertically illuminated photodetectors targeting ranging applications

Pascal Rustige, Patrick Runge, Martin Schell, Francisco M. Soares, Jan Krause

This paper proposes a novel approach for coherent detection with double-side vertically illuminated photodetectors. Signal and local oscillator are injected collinearly from opposite sides of the photodetector chip. The concept inherently...


February 2022

Characterization, Monitoring, and Mitigation of Standard C-Band Transceivers I/Q Imbalance in Multiband Systems

Gabriele Di Rosa, Colja Schubert, Ronald Freund, Johannes Fischer, Andre Richter, Robert Emmerich, Matheus Ribeiro Sena

To keep up with the rapid growth in global traffic, next-generation optical communication networks aim to vastly increase capacity by exploiting a larger optical transmission window covering the S-C-L-band. To reuse current commercially available...


February 2022

Imposing Temporal Consistency on Deep Monocular Body Shape and Pose Estimation

Alexandra Zimmer, Peter Eisert, Anna Hilsmann, Wieland Morgenstern

We present a solution for Accurate and temporally consistent modeling of human performances from video sequences. In detail, we derive parameters of a sequence of body models, representing shape and motion of a person, including jaw poses, facial...


February 2022

From Explanations to Segmentation: Using Explainable AI for Image Segmentation

Johannes Wolf Künzel, Peter Eisert, Anna Hilsmann, Clemens Peter Seibold

The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision. In...


February 2022

Combining Local and Global Pose Estimation for Precise Tracking of Similar Objects

Niklas Gard, Peter Eisert, Anna Hilsmann

We present a multi-object 6D detection and tracking pipeline for potentially similar and non-textured objects. The combination of a convolutional neural network for object classification and rough pose estimation with a local pose refinement and...


February 2022

Overview of the Neural Network Compression and Representation (NNR) Standard

Heiner Kirchhoffer, Karsten Müller, Werner Bailer, Fabien Racape, Wojciech Samek, Shan Liu, Miska M. Hannuksela, Paul Haase, Hamed Rezazadegan-Tavakoli, Francesco Cricri, Emre Aksu, Wei Jiang, Wei Wang, Swayambhoo Jain, Shahab Hamidi-Rad

Neural Network Coding and Representation (NNR) is the first international standard for efficient compression of neural networks. The NNR standard contains quantization and an arithmetic coding scheme as core encoding and decoding technologies, as...



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