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Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy


Jun 24, 2021
Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin

* 10 pages, 3 figures 

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Explanation-Guided Training for Cross-Domain Few-Shot Classification


Jul 17, 2020
Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder


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Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution


Apr 22, 2020
Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder

* 8 pages, 3 figures 

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Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond


Mar 17, 2020
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller

* 24 pages, 18 figures 

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Understanding Image Captioning Models beyond Visualizing Attention


Jan 22, 2020
Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Alexander Binder


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Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed


Dec 22, 2019
Christopher J. Anders, Talmaj Marinč, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin

* 16 pages, 14 figures 

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Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning


Dec 18, 2019
Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek

* 24 pages, 8 figures 

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On the Understanding and Interpretation of Machine Learning Predictions in Clinical Gait Analysis Using Explainable Artificial Intelligence


Dec 16, 2019
Fabian Horst, Djordje Slijepcevic, Sebastian Lapuschkin, Anna-Maria Raberger, Matthias Zeppelzauer, Wojciech Samek, Christian Breiteneder, Wolfgang I. Schöllhorn, Brian Horsak

* 35 pages, 6 figures, 2 tables, 24 supplementary figures 

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Towards best practice in explaining neural network decisions with LRP


Oct 22, 2019
Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin

* 5 pages, 3 figures, 1 table 

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Resolving challenges in deep learning-based analyses of histopathological images using explanation methods


Aug 15, 2019
Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, Alexander Binder


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Unmasking Clever Hans Predictors and Assessing What Machines Really Learn


Feb 26, 2019
Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller

* Accepted for publication in Nature Communications 

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What is Unique in Individual Gait Patterns? Understanding and Interpreting Deep Learning in Gait Analysis


Aug 13, 2018
Fabian Horst, Sebastian Lapuschkin, Wojciech Samek, Klaus-Robert Müller, Wolfgang I. Schöllhorn

* 17 pages (23 pages including references, 24 pages including references and auxiliary statements, 33 pages including references, auxiliary statements and and supplementary material). 5 figures, 3 tables, 4 supplementary figures, 9 supplementary tables. Under review at Scientific Reports 

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iNNvestigate neural networks!


Aug 13, 2018
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans


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Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals


Jul 09, 2018
Sören Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert Müller, Wojciech Samek

* 6 pages, 4 figures 

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Understanding and Comparing Deep Neural Networks for Age and Gender Classification


Aug 25, 2017
Sebastian Lapuschkin, Alexander Binder, Klaus-Robert Müller, Wojciech Samek

* 8 pages, 5 figures, 5 tables. Presented at ICCV 2017 Workshop: 7th IEEE International Workshop on Analysis and Modeling of Faces and Gestures 

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Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation


Nov 24, 2016
Wojciech Samek, Grégoire Montavon, Alexander Binder, Sebastian Lapuschkin, Klaus-Robert Müller

* Presented at NIPS 2016 Workshop on Interpretable Machine Learning in Complex Systems 

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