Aktuelle Publikationen

Juli 2024

Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations

Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin, Reduan Achtibat

With PCX, we introduce a method that summarizes similar single explanations via prototypical ones. As such, we can understand the whole model behavior quickly and in detail. PCX further allows to validate individual predictions by communicating...


Juli 2024

AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers

Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Sayed M. V. Hatefi, Aakriti Jain

Our new method, AttnLRP, is the first to faithfully and holistically attribute not only input but also latent representations of transformer models with the computational efficiency similar to a single backward pass. We demonstrate that our...


Juli 2024

Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification

Christian Tinauer, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Reduan Achtibat, Frederik Pahde, Anna Damulina, Maximilian Sackl, Martin Soellradl, Reinhold Schmidt, Stefan Ropele, Christian Langkammer

While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investigated. We separated Alzheimer's patients (n=117) from normal controls (n=219) by...


Juli 2024

PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits

Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin, Johanna Vielhaben, Erblina Purelku

Neurons in deep neural networks can act polysemantically, meaning that they encode for multiple (unrelated) features. As such, understanding the inner workings of machine learning models becomes more difficult. We present PURE to turn...


Juli 2024

Model guidance via explanations turns image classifiers into segmentation models

Xiaoyan Yu, Wojciech Samek, Marina M.-C. Höhne, Dagmar Kainmüller, Jannik Franzen

Heatmaps generated on inputs of image classification networks via explainable AI methods have been observed to resemble segmentations of input images in many cases. We apply the "Right for the Right Reason" paradigm of imposing additional losses...


Juli 2024

Distributed Convex Optimization “Over-the-Air” in Dynamic Environments

Navneet Agrawal, Slawomir Stanczak, Renato L. G. Cavalcante, Masahiro Yukawa

The paper proposes a class of distributed algorithms where the consensus step is implemented in a scalable and truly decentralized fashion using a novel communication protocol based on the “over-the-air” function computation (OTA-C)...


Juni 2024

Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays

Lorenzo Miretti, Slawomir Stanczak

Centralized or distributed precoding? This is perhaps the most heated debate in the Cell-free Massive MIMO literature. However, in this work we argue that the best option may actually be a mix of the two. The reason is that centralized precoding,...


Juni 2024

Towards Bridging the Gap between Near and Far-Field Characterizations of the Wireless Channel

Navneet Agrawal, Slawomir Stanczak, Renato L. G. Cavalcante, Ehsan Tohidi

Exploring near-field propagation is vital for 6G technologies like intelligent reflecting surfaces (IRS). Unlike far-field models, near-field models offer accuracy critical for applications such as beamforming and multiple-access, enhancing...


Juni 2024

Explainable AI for Time Series via Virtual Inspection Layers

Johanna Vielhaben, Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin

For time series data, where the input itself is often not interpretable, dedicated XAI research is scarce. In this work, we put forward a virtual inspection layer for transforming the time series to an interpretable representation and allows to...


Juni 2024

Wavelength Tunable, Polymer-Based Arrayed Waveguide Gratings for Hybrid Integration

Martin Kresse, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Tianwen Qian, Madeleine Weigel, Jakob Reck, Klara Mihov, Philipp Winklhofer

We present a hybrid integrated photonic circuit with tunable arrayed waveguide gratings (AWGs) as (DE-)MUX stages for optical modulators for use in parallel convolution processing. The simulated and fabricated AWGs have 16 outputs with 500 GHz...


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