Towards Best Practice in Explaining Neural Network Decisions with LRP

22 October 2019

Papers citing "Towards Best Practice in Explaining Neural Network Decisions with LRP"

31 / 31 papers shown

Title
Investigating the Relationship Between Debiasing and Artifact Removal using Saliency Maps Lukasz Sztukiewicz Ignacy Stepka Michał Wiliński Jerzy Stefanowski 41 0 0 28 Feb 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 100 0 0 30 Dec 2024
Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation Paulo Yanez Sarmiento Simon Witzke Nadja Klein Bernhard Y. Renard FAtt AAML 40 0 0 22 Apr 2024
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition Sangyu Han Yearim Kim Nojun Kwak AAML 29 1 0 25 Jan 2024
Prototypical Self-Explainable Models Without Re-training Srishti Gautam Ahcène Boubekki Marina M.-C. Höhne Michael C. Kampffmeyer 31 2 0 13 Dec 2023
XAI-based Comparison of Input Representations for Audio Event Classification A. Frommholz Fabian Seipel Sebastian Lapuschkin Wojciech Samek Johanna Vielhaben AAML AI4TS 27 6 0 27 Apr 2023
Explainable AI for Time Series via Virtual Inspection Layers Johanna Vielhaben Sebastian Lapuschkin G. Montavon Wojciech Samek XAI AI4TS 18 25 0 11 Mar 2023
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus Anna Hedström P. Bommer Kristoffer K. Wickstrom Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne 37 21 0 14 Feb 2023
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria Theresa Bender J. Beinecke D. Krefting Carolin Müller Henning Dathe T. Seidler Nicolai Spicher Anne-Christin Hauschild FAtt 16 25 0 03 Nov 2022
Local Interpretable Model Agnostic Shap Explanations for machine learning models P. Aditya M. Pal FAtt 34 6 0 10 Oct 2022
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces Iñigo López-Riobóo Botana Carlos Eiras-Franco Julio César Hernández Castro Amparo Alonso-Betanzos 21 0 0 09 Sep 2022
Towards ML Methods for Biodiversity: A Novel Wild Bee Dataset and Evaluations of XAI Methods for ML-Assisted Rare Species Annotations Teodor Chiaburu F. Biessmann Frank Haußer 35 2 0 15 Jun 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 30 131 0 07 Jun 2022
Comparing interpretation methods in mental state decoding analyses with deep learning models A. Thomas Christopher Ré R. Poldrack AI4CE 13 2 0 31 May 2022
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI Sami Ede Serop Baghdadlian Leander Weber A. Nguyen Dario Zanca Wojciech Samek Sebastian Lapuschkin CLL 27 6 0 04 May 2022
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond Anna Hedström Leander Weber Dilyara Bareeva Daniel G. Krakowczyk Franz Motzkus Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne XAI ELM 21 168 0 14 Feb 2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience Antonios Mamalakis E. Barnes I. Ebert‐Uphoff 23 73 0 07 Feb 2022
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence Frederik Pahde Maximilian Dreyer Leander Weber Moritz Weckbecker Christopher J. Anders Thomas Wiegand Wojciech Samek Sebastian Lapuschkin 60 7 0 07 Feb 2022
Brain Structural Saliency Over The Ages Daniel Taylor Jonathan Shock Deshendran Moodley J. Ipser M. Treder FAtt 13 1 0 12 Jan 2022
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 29 65 0 15 Nov 2021
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 27 49 0 27 Aug 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 34 25 0 23 Aug 2021
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 29 64 0 24 Jun 2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 28 75 0 18 Mar 2021
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones Andrew P. Creagh F. Lipsmeier M. Lindemann M. D. Vos 24 17 0 16 Mar 2021
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease M. Dyrba Moritz Hanzig S. Altenstein Sebastian Bader Tommaso Ballarini ... B. Ertl-Wagner M. Wagner J. Wiltfang F. Jessen S. Teipel FAtt MedIm 34 51 0 18 Dec 2020
How Much Can I Trust You? -- Quantifying Uncertainties in Explaining Neural Networks Kirill Bykov Marina M.-C. Höhne Klaus-Robert Muller Shinichi Nakajima Marius Kloft UQCV FAtt 27 31 0 16 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 44 82 0 17 Mar 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 21 150 0 16 Mar 2020
When Explanations Lie: Why Many Modified BP Attributions Fail Leon Sixt Maximilian Granz Tim Landgraf BDL FAtt XAI 13 132 0 20 Dec 2019
On the Explanation of Machine Learning Predictions in Clinical Gait Analysis D. Slijepcevic Fabian Horst Sebastian Lapuschkin Anna-Maria Raberger Matthias Zeppelzauer Wojciech Samek C. Breiteneder W. Schöllhorn B. Horsak 36 50 0 16 Dec 2019