Evaluating the visualization of what a Deep Neural Network has learned

21 September 2015

Papers citing "Evaluating the visualization of what a Deep Neural Network has learned"

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Title
ERASER: A Benchmark to Evaluate Rationalized NLP Models Jay DeYoung Sarthak Jain Nazneen Rajani Eric P. Lehman Caiming Xiong R. Socher Byron C. Wallace 24 626 0 08 Nov 2019
Explanation by Progressive Exaggeration Sumedha Singla Brian Pollack Junxiang Chen Kayhan Batmanghelich FAtt MedIm 4 103 0 01 Nov 2019
Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models L. Brocki N. C. Chung FAtt 20 21 0 29 Oct 2019
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks Aya Abdelsalam Ismail Mohamed K. Gunady L. Pessoa H. C. Bravo S. Feizi AI4TS 25 50 0 27 Oct 2019
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 14 148 0 22 Oct 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019
Explaining image classifiers by removing input features using generative models Chirag Agarwal Anh Totti Nguyen FAtt 28 15 0 09 Oct 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 32 436 0 26 Sep 2019
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 16 79 0 25 Sep 2019
Towards a Rigorous Evaluation of XAI Methods on Time Series U. Schlegel Hiba Arnout Mennatallah El-Assady Daniela Oelke Daniel A. Keim XAI AI4TS 15 169 0 16 Sep 2019
Explainable Deep Learning for Video Recognition Tasks: A Framework & Recommendations Liam Hiley Alun D. Preece Y. Hicks XAI 11 15 0 07 Sep 2019
Neural Cognitive Diagnosis for Intelligent Education Systems Fei-Yue Wang Qi Liu Enhong Chen Zhenya Huang Yuying Chen Yu Yin Zai Huang Shijin Wang AI4Ed 13 225 0 23 Aug 2019
Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems Bao Gia Doan Ehsan Abbasnejad D. Ranasinghe AAML 11 66 0 09 Aug 2019
Benchmarking Attribution Methods with Relative Feature Importance Mengjiao Yang Been Kim FAtt XAI 16 140 0 23 Jul 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 42 1,414 0 17 Jul 2019
Saliency Maps Generation for Automatic Text Summarization David Tuckey Krysia Broda A. Russo FAtt 10 3 0 12 Jul 2019
Global Aggregations of Local Explanations for Black Box models I. V. D. Linden H. Haned Evangelos Kanoulas FAtt 11 63 0 05 Jul 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 20 328 0 19 Jun 2019
From Clustering to Cluster Explanations via Neural Networks Jacob R. Kauffmann Malte Esders Lukas Ruff G. Montavon Wojciech Samek K. Müller 24 68 0 18 Jun 2019
Model Agnostic Contrastive Explanations for Structured Data Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin-Yu Chen Karthikeyan Shanmugam Ruchi Puri FAtt 20 82 0 31 May 2019
Leveraging Latent Features for Local Explanations Ronny Luss Pin-Yu Chen Amit Dhurandhar P. Sattigeri Yunfeng Zhang Karthikeyan Shanmugam Chun-Chen Tu FAtt 41 37 0 29 May 2019
A Rate-Distortion Framework for Explaining Neural Network Decisions Jan Macdonald S. Wäldchen Sascha Hauch Gitta Kutyniok 11 39 0 27 May 2019
Predicting Model Failure using Saliency Maps in Autonomous Driving Systems Sina Mohseni Akshay V. Jagadeesh Zhangyang Wang 11 13 0 19 May 2019
Full-Gradient Representation for Neural Network Visualization Suraj Srinivas F. Fleuret MILM FAtt 8 268 0 02 May 2019
Evaluating Recurrent Neural Network Explanations L. Arras Ahmed Osman K. Müller Wojciech Samek XAI FAtt 8 88 0 26 Apr 2019
Analysis and Visualization of Deep Neural Networks in Device-Free Wi-Fi Indoor Localization Shing-Jiuan Liu Ronald Y. Chang Feng-Tsun Chien 14 21 0 23 Apr 2019
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation Fabian Eitel Emily Soehler J. Bellmann-Strobl A. Brandt K. Ruprecht ... M. Weygandt J. Haynes M. Scheel Friedemann Paul K. Ritter 19 131 0 18 Apr 2019
Software and application patterns for explanation methods Maximilian Alber 25 11 0 09 Apr 2019
A Categorisation of Post-hoc Explanations for Predictive Models John Mitros Brian Mac Namee XAI CML 14 0 0 04 Apr 2019
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks Woo-Jeoung Nam Shir Gur Jaesik Choi Lior Wolf Seong-Whan Lee FAtt 6 99 0 01 Apr 2019
Bridging Adversarial Robustness and Gradient Interpretability Beomsu Kim Junghoon Seo Taegyun Jeon AAML 6 39 0 27 Mar 2019
Explaining Anomalies Detected by Autoencoders Using SHAP Liat Antwarg Ronnie Mindlin Miller Bracha Shapira Lior Rokach FAtt TDI 11 86 0 06 Mar 2019
Aggregating explanation methods for stable and robust explainability Laura Rieger Lars Kai Hansen AAML FAtt 32 11 0 01 Mar 2019
Deep learning in bioinformatics: introduction, application, and perspective in big data era Yu-Hu Li Chao Huang Lizhong Ding Zhongxiao Li Yijie Pan Xin Gao AI4CE 21 295 0 28 Feb 2019
A novel method for extracting interpretable knowledge from a spiking neural classifier with time-varying synaptic weights Abeegithan Jeyasothy Suresh Sundaram Savitha Ramasamy N. Sundararajan 4 4 0 28 Feb 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 17 996 0 26 Feb 2019
Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps Beomsu Kim Junghoon Seo Seunghyun Jeon Jamyoung Koo J. Choe Taegyun Jeon FAtt 16 69 0 13 Feb 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 8 201 0 06 Feb 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI Shane T. Mueller R. Hoffman W. Clancey Abigail Emrey Gary Klein XAI 10 284 0 05 Feb 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 28 446 0 27 Jan 2019
Quantifying Interpretability and Trust in Machine Learning Systems Philipp Schmidt F. Biessmann 6 111 0 20 Jan 2019
Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks Phillip E. Pope Soheil Kolouri Mohammad Rostami Charles E. Martin Heiko Hoffmann GNN 33 14 0 01 Dec 2018
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Sina Mohseni Niloofar Zarei Eric D. Ragan 23 102 0 28 Nov 2018
An Overview of Computational Approaches for Interpretation Analysis Philipp Blandfort Jörn Hees D. Patton 21 2 0 09 Nov 2018
Looking Deeper into Deep Learning Model: Attribution-based Explanations of TextCNN Wenting Xiong Iftitahu Ni'mah Juan M. G. Huesca Werner van Ipenburg Jan Veldsink Mykola Pechenizkiy FAtt 6 7 0 08 Nov 2018
LAMVI-2: A Visual Tool for Comparing and Tuning Word Embedding Models Xin Rong Joshua Luckson Eytan Adar VLM 8 2 0 22 Oct 2018
Logic Negation with Spiking Neural P Systems Daniel Rodríguez-Chavarría Miguel A. Gutiérrez-Naranjo J. Borrego-Díaz NAI 11 3 0 18 Oct 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 37 1,927 0 08 Oct 2018
Explaining the Unique Nature of Individual Gait Patterns with Deep Learning Fabian Horst Sebastian Lapuschkin Wojciech Samek K. Müller W. Schöllhorn AI4CE 15 207 0 13 Aug 2018
iNNvestigate neural networks! Maximilian Alber Sebastian Lapuschkin P. Seegerer Miriam Hagele Kristof T. Schütt G. Montavon Wojciech Samek K. Müller Sven Dähne Pieter-Jan Kindermans 8 348 0 13 Aug 2018