Finding and Removing Clever Hans: Using Explanation Methods to Debug and
Improve Deep Models

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Finding and Removing Clever Hans: Using Explanation Methods to Debug and Improve Deep Models

22 December 2019

Christopher J. Anders

Sebastian Lapuschkin

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Papers citing "Finding and Removing Clever Hans: Using Explanation Methods to Debug and Improve Deep Models"

12 / 12 papers shown

Title
Prototypical Self-Explainable Models Without Re-training Srishti Gautam Ahcène Boubekki Marina M.-C. Höhne Michael C. Kampffmeyer 99 2 0 13 Dec 2023
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model Srishti Gautam Ahcène Boubekki Stine Hansen Suaiba Amina Salahuddin Robert Jenssen Marina M.-C. Höhne Michael C. Kampffmeyer 79 38 0 15 Oct 2022
Detecting Backdoor Poisoning Attacks on Deep Neural Networks by Heatmap Clustering Lukas Schulth Christian Berghoff Matthias Neu AAML 63 5 0 27 Apr 2022
A Typology for Exploring the Mitigation of Shortcut Behavior Felix Friedrich Wolfgang Stammer P. Schramowski Kristian Kersting LLMAG 62 7 0 04 Mar 2022
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 68 49 0 27 Aug 2021
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 96 64 0 18 Dec 2020
Split and Expand: An inference-time improvement for Weakly Supervised Cell Instance Segmentation Lin Geng Foo Rui En Ho Jiamei Sun Alexander Binder 50 0 0 21 Jul 2020
Towards explainable classifiers using the counterfactual approach -- global explanations for discovering bias in data Agnieszka Mikołajczyk M. Grochowski Arkadiusz Kwasigroch FAtt CML 39 3 0 05 May 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 145 83 0 17 Mar 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 152 213 0 15 Jan 2020
Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models Jiamei Sun Sebastian Lapuschkin Wojciech Samek Alexander Binder FAtt 98 30 0 04 Jan 2020
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 106 150 0 22 Oct 2019