Recent publications

March 2024

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space

Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin, Christopher J. Anders, Frederik Pahde

We present a novel method ensuring the right reasons on the concept level by reducing the model's sensitivity towards biases through the gradient. When modeling biases via Concept Activation Vectors, we highlight the importance of choosing robust...


March 2024

Sparse Aperiodic Optical Phased Arrays on Polymer Integration Platform

Adam Raptakis, Christos Kouloumentas, Norbert Keil, Moritz Kleinert, Hercules Avramopoulos, Panos Groumas, Lefteris Gounaridis, Christos Tsokos, Madeleine Weigel, Efstathios Andrianopoulos, Georgios Lymperakis

Solid-state optical beam-steering utilizing polymer waveguides as edge emitters to form optical phased arrays (OPAs) with aperiodic spacing for operation at 1550 nm is demonstrated for the first time. Power consumption of 1.28 mW/? per channel is...


February 2024

Animating NeRFs from Texture Space: A Framework for Pose-Dependent Rendering of Human Performances

Paul Knoll, Peter Eisert, Anna Hilsmann, Wieland Morgenstern

We introduce a novel NeRF-based framework for pose-dependent rendering of human performances where the radiance field is warped around an SMPL body mesh, thereby creating a new surface-aligned representation. Our representation can be animated...


February 2024

Efficient and Accurate Hyperspectral Image Demosaicing with Neural Network Architectures

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Thomas Wittenberg, Lara Wallburg, Stefan Göb

This study investigates the effectiveness of neural network architectures in hyperspectral image demosaicing. We introduce a range of network models and modifications, and compare them with classical interpolation methods and existing reference...


February 2024

Multi-View Inversion for 3D-aware Generative Adversarial Networks

Florian Tim Barthel, Peter Eisert, Anna Hilsmann

Our method builds on existing state-of-the-art 3D GAN inversion techniques to allow for consistent and simultaneous inversion of multiple views of the same subject. We employ a multi-latent extension to handle inconsistencies present in dynamic...


February 2024

Generative Texture Super-Resolution via Differential Rendering

Milena Teresa Bagdasarian, Peter Eisert, Anna Hilsmann

We propose a generative deep learning network for texture map super-resolution using a differentiable renderer and calibrated reference images. Combining a super-resolution generative adversarial network (GAN) with differentiable rendering, we...


February 2024

Towards Better Morphed Face Images Without Ghosting Artifacts

Clemens Peter Seibold, Anna Hilsmann

We propose a method for automatic prevention of ghosting artifacts based on a pixel-wise alignment during morph generation. We evaluate our proposed method on state-of-the-art detectors and show that our morphs are harder to detect, particularly,...


February 2024

Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene Reconstruction

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Jost Triller

We present a novel approach combining two calibrated multispectral real-time capable snapshot cameras, covering different spectral ranges, into a stereo-system. Therefore, a hyperspectral data-cube can be continuously captured. The combined use...


February 2024

Little or No Equalization is Needed in Energy-Efficient Sub-THz Mobile Access

Lorenzo Miretti, Slawomir Stanczak, Wilhelm Keusgen, Michael Peter, Giuseppe Caire, Taro Eichler, Thomas Kühne, Alper Schultze

We validate experimentally the claim that, in sub-THz mobile access networks, single-carrier or low-number-of-subcarriers modulations are very attractive competitors to the dramatically more complex and energy-inefficient traditional...


February 2024

Polymer Waveguide Sensor Based on Evanescent Bragg Grating for Lab-on-a-Chip Applications

Zhenyu Zhang, Wolfgang Schade, Martin Angelmahr, Ahmad Abdalwareth, Günter Flachenecker

This work integrates an evanescent Bragg grating sensor into a polymer waveguide with microchannels. The sensor, built with epoxide-based polymers, is characterized through chemical applications. Temperature sensitivity is demonstrated (-47.75...


February 2024

Insights into the inner workings of transformer models for protein function prediction

Markus Wenzel, Nils Strodthoff, Erik Grüner

We explored how explainable artificial intelligence (XAI) can help to shed light into the inner workings of neural networks for protein function prediction, by extending the widely used XAI method of integrated gradients such that latent...


February 2024

Semantic Communication for Edge Intelligence: Theoretical Foundations and Implications on Protocols

Zoran Utkovski, Slawomir Stanczak, Johannes Dommel, Giuseppe Caire, Andrea Munari, Pin-Hsun Lin, Max Franke, André C. Drummond

Recent attention to semantic communication, driven by task-oriented solutions, aims to optimize resource use. Despite perceived efficiency gains, few practical implementations exist. This paper revisits theoretical foundations, emphasizing...


January 2024

Towards an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets

Rodrigo Hernangómez, Slawomir Stanczak, Martin Kasparick, Gerhard Fettweis, Daniel Schäufele, Rafail Ismayilov, Oscar Dario Ramos-Cantor, Hugues Tchouankem, Philipp Geuer, Alexandros Palaois, Cara Watermann, Mohammad Parvini, Anton Krause, Thomas Neugebauer, Jose Leon Calvo, Bo Chen

We present iV2V and iV2i+, two machine-learning datasets for industrial wireless communication. The datasets cover sidelink and cellular communication involving autonomous robots together with localization and sensing data, which can be used to...


January 2024

Integrated heterodyne laser Doppler vibrometer based on stress-optic frequency shift in silicon nitride

Adam Raptakis, Christos Kouloumentas, Norbert Keil, Moritz Kleinert, Hercules Avramopoulos, Panos Groumas, Lefteris Gounaridis, Christos Tsokos, Rene G. Heidemann, Madeleine Weigel, Efstathios Andrianopoulos, Jörn P. Epping, Thi Lan Anh Tran, Thomas Aukes, Marco Wolfer, Alexander Draebenstedt, Nikos Lyras, Dimitrios Nikolaidis, Elias Mylonas, Nikolaos Baxevanakis, Roberto Pessina, Erik Schreuder, Matthijn Dekkers, Volker Seyfried

We demonstrate a compact heterodyne Laser Doppler Vibrometer (LDV) based on the realization of optical frequency shift in the silicon nitride photonic integration ! platform (TriPleX). The system comprises a dual-polarization coherent detector...


January 2024

Hybrid integration of Polymer PICs and InP optoelectronics for WDM and SDM terabit intra-DC optical interconnects

Efstathios Andrianopoulos, Christos Kouloumentas, Patrick Runge, Norbert Keil, Martin Moehrle, Ute Troppenz, Annachiara Pagano, David de Felipe Mesquida, Michael Theurer, Martin Kresse, Hercules Avramopoulos, Anna Chiado Piat, Panos Groumas, Christos Tsokos, Paraskevas Bakopoulos, Madeleine Weigel, Maria Massaouti, Zerihun Tegegne, Giorgos Megas

This paper presents a hybrid photonic integration concept based on the use of a polymer motherboard, InP EML arrays and InP PD arrays to realize WDM and SDM Terabit optical engines operating at 100-Gb/s or even at 20! 0-Gb/s per lane. The optical...


January 2024

Highly Sensitive Switchable Sensors for Hydroxide on Glass Surfaces Based on Isoquinolinium-Quinolinium-substituted Acetylenes

Alexander Tombrink, Eike Hübner, Felix Lederle, Jan C. Namyslo, Andreas Schmidt, Sven Nagorny, Sviatoslav Batsyts, Jörg Adams

Bi-substituted acetylenes with a quinolinium and an isoquinolinium substituent are described, which reversibly form intensely colored adducts with O-nucleophiles and thus enable the detection of >0,5 ppm hydroxide on the surfaces of various...


January 2024

AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark

Sören Becker, Klaus-Robert Müller, Wojciech Samek, Sebastian Lapuschkin, Marcel Ackermann, Johanna Vielhaben

Explainable Artificial Intelligence (XAI) is targeted at understanding how models perform feature selection and derive their classification decisions. This paper explores post-hoc explanations for deep neural networks in the audio domain....


December 2023

A Performance Comparison of OFDM and Pulsed PHY Modulations in Optical Wireless Communications

Malte Hinrichs, Volker Jungnickel, Ronald Freund, Anagnostis Paraskevopoulos, Maria Pontes, Marcelo Segatto, Jair Silva, Helder Rocha, Wesley Costa

Experimental tests of the OFDM and OOK-based PHYs in the Li-Fi standard IEEE 802.15.13-2023 show that the higher peak data rates of OFDM and the longer reach of OOK make them suitable for deployment in down- and uplink use cases, respectively.


December 2023

Full-Duplex Operation of ISAC: Self-Interference Reduction from the Lens of IRS

Ehsan Tohidi, Slawomir Stanczak, Ramez Askar, Zoran Utkovski

This paper addresses the self-interference problem in full duplex operation by leveraging an intelligent reflecting surface (IRS) to provide spatial separation of the transmitted and the received (i.e. reflected) signal in a monostatic sensing...


December 2023

4 Gbit/s optical wireless communication with high-power transmitter

Malte Hinrichs, Volker Jungnickel, Martin Schubert, Ronald Freund, Dominic Schulz, Ronald Böhnke, Giulio Boniello, Mariana Lyra Silveira, Wen Xu

We demonstrate data rates up to 4 Gbit/s with a VCSEL-based transmitter prototype using pulsed on-off-keying modulation for high-speed LiFi with a large coverage area.


December 2023

L4S Congestion Control Algorithm for Interactive Low Latency Applications over 5G

Jangwoo Son, Thomas Schierl, Cornelius Hellge, Yago Sanchez de la Fuente, Christian Hampe, Dominik Schnieders

In recent years, immersive applications such as Cloud XR have emerged, which require very low latency to ensure a high quality of experience. This paper presents a congestion control algorithm combined with L4S to achieve stable and low latency...


December 2023

Guard-ring free InGaAs/InP single photon avalanche diodes for C-band quantum communication

Pascal Rustige, Patrick Runge, Martin Schell, Jan Krause, Lorenz Eckoldt

We present a guard-ring free InGaAs/InP single photon avalanche diode with 20 µm diameter for the optical C-band. At 225 K, 25.6 µs dead time and 17% detection efficiency, the dark count rate is 3 kcps with 0.5% afterpulsing probability. This...


November 2023

From Empirical Measurements to Augmented Data Rates: A Machine Learning Approach for MCS Adaptation in Sidelink Communication

Asif Abdullah Rokoni, Slawomir Stanczak, Martin Kasparick, Daniel Schäufele

Due to the lack of a feedback channel in the C-V2X sidelink, finding a suitable MCS level is a difficult task. In this paper, we propose an ML approach that uses quantile prediction to predict the MCS level with the highest achievable data rate....


November 2023

Hybrid integration of Polymer PICs and InP optoelectronics for WDM and SDM terabit intra-DC optical interconnects

Efstathios Andrianopoulos, Christos Kouloumentas, Patrick Runge, Norbert Keil, Martin Moehrle, Ute Troppenz, Annachiara Pagano, David de Felipe Mesquida, Michael Theurer, Martin Kresse, Hercules Avramopoulos, Anna Chiado Piat, Panos Groumas, Christos Tsokos, Paraskevas Bakopoulos, Madeleine Weigel, Maria Massaouti, Zerihun Tegegne, Giorgos Megas

This paper presents a hybrid photonic integration concept based on the use of a polymer motherboard, InP EML arrays and InP PD arrays to realize WDM and SDM Terabit optical engines operating at 100-Gb/s or even at 20! 0-Gb/s per lane. The optical...


November 2023

Design and Characterization of Dispersion-Tailored Silicon Strip Waveguide toward Wideband Wavelength Conversion

Hidenobu Muranaka, Tomoyuki Kato, Shun Okada, Tokuharu Kimura, Yu Tanaka, Tsuyoshi Yamamoto, Isaac Sackey, Gregor Ronniger, Robert Elschner, Carsten Schmidt-Langhorst, Takeshi Hoshida

One of cost-effective ways to increase the transmission capacity of current standard wavelength division multiplexing (WDM) transmission systems is to use a wavelength band other than the C-band to transmit in multi-band. We proposed the concept...


November 2023

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations

Alexander Binder, Klaus-Robert Müller, Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Leander Weber

While the evaluation of explanations is an important step towards trustworthy models, it needs to be done carefully, and the employed metrics need to be well-understood. Specifically model randomization testing is often overestimated and regarded...


November 2023

Optimizing Explanations by Network Canonization and Hyperparameter Search

Frederick Pahde, Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Galip Ümit Yolcu

Rule-based and modified backpropagation XAI methods struggle with innovative layer building blocks and implementation-invariance issues. In this work we propose canonizations for popular deep neural network architectures and introduce an XAI...


November 2023

Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations

Maximilian Dreyer, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin, Reduan Achtibat

Applying traditional post-hoc attribution methods to segmentation or object detection predictors offers only limited insights, as the obtained feature attribution maps at input level typically resemble the models' predicted segmentation mask or...


November 2023

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models

Frederick Pahde, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer

State-of-the-art machine learning models often learn spurious correlations embedded in the training data. This poses risks when deploying these models for high-stake decision-making, such as in medical applications like skin cancer detection. To...


November 2023

Channel estimation with Zadoff–Chu sequences in the presence of phase errors

Sven Wittig, Wilhelm Keusgen, Michael Peter

Due to their perfect periodic autocorrelation property, Zadoff–Chu sequences are often used as stimulus signals in the measurement of radio channel responses. In this letter, the cross-correlation of a linear shift-invariant system's response to...


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