Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models

16 May 2018

Papers citing "Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models"

9 / 9 papers shown

Title
On Root Cause Localization and Anomaly Mitigation through Causal Inference Xiao Han Lu Zhang Yongkai Wu Shuhan Yuan 26 7 0 08 Dec 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data Timur Sattarov Dayananda Herurkar Jörn Hees 27 8 0 21 Sep 2022
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 28 63 0 21 Dec 2021
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications Dongqi Han Zhiliang Wang Wenqi Chen Ying Zhong Su Wang Han Zhang Jiahai Yang Xingang Shi Xia Yin AAML 16 76 0 23 Sep 2021
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 11 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 36 82 0 17 Mar 2020
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 21 435 0 26 Sep 2019
Explaining Anomalies Detected by Autoencoders Using SHAP Liat Antwarg Ronnie Mindlin Miller Bracha Shapira L. Rokach FAtt TDI 11 86 0 06 Mar 2019
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning Oren Z. Kraus Lei Jimmy Ba B. Frey 159 391 0 17 Nov 2015