Papers citing 'Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI'

Title
Deep Learning for Road Traffic Forecasting: Does it Make a Difference? Eric L. Manibardo I. Laña Javier Del Ser AI4TS 190 85 0 02 Dec 2020
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training Andrei Margeloiu Nikola Simidjievski M. Jamnik Adrian Weller GAN AAML MedIm FAtt 100 20 0 02 Dec 2020
Reviewing the Need for Explainable Artificial Intelligence (xAI)Hawaii International Conference on System Sciences (HICSS), 2020 Julie Gerlings Arisa Shollo Ioanna D. Constantiou 316 79 0 02 Dec 2020
Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Fair and Explainable Automatic Recruitment Alfonso Ortega Julian Fierrez Aythami Morales Zilong Wang Tony Ribeiro 197 14 0 01 Dec 2020
Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation hsan Ullah André Ríos Vaibhav Gala Susan Mckeever FAtt 158 10 0 26 Nov 2020
Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems Adriano Lucieri Muhammad Naseer Bajwa Andreas Dengel Sheraz Ahmed 256 13 0 26 Nov 2020
Quantifying Explainers of Graph Neural Networks in Computational PathologyComputer Vision and Pattern Recognition (CVPR), 2020 Guillaume Jaume Pushpak Pati Behzad Bozorgtabar Antonio Foncubierta-Rodríguez Florinda Feroce A. Anniciello T. Rau Jean-Philippe Thiran M. Gabrani O. Goksel FAtt 159 89 0 25 Nov 2020
PSD2 Explainable AI Model for Credit Scoring N. Torrent Giorgio Visani Engineering 150 1 0 20 Nov 2020
Qualitative Investigation in Explainable Artificial Intelligence: A Bit More Insight from Social Science Adam J. Johs Denise E. Agosto Rosina O. Weber 172 7 0 13 Nov 2020
Unsupervised Explanation Generation for Machine Reading Comprehension Yiming Cui Ting Liu Shijin Wang Guoping Hu LRM 93 3 0 13 Nov 2020
Interpretable collaborative data analysis on distributed data A. Imakura Hiroaki Inaba Yukihiko Okada Tetsuya Sakurai FedML 83 27 0 09 Nov 2020
Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification Agus Sudjianto William Knauth Rahul Singh Zebin Yang Aijun Zhang FAtt 200 50 0 08 Nov 2020
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition Meike Nauta Annemarie Jutte Jesper C. Provoost C. Seifert FAtt 276 74 0 05 Nov 2020
Towards Personalized Explanation of Robot Path Planning via User Feedback Kayla Boggess Shenghui Chen Lu Feng 112 4 0 01 Nov 2020
Interpretable Machine Learning Models for Predicting and Explaining Vehicle Fuel Consumption AnomaliesEngineering applications of artificial intelligence (EAAI), 2020 A. Barbado Óscar Corcho 251 15 0 28 Oct 2020
Now You See Me (CME): Concept-based Model ExtractionInternational Conference on Information and Knowledge Management (CIKM), 2020 Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lio Adrian Weller 85 81 0 25 Oct 2020
Abduction and Argumentation for Explainable Machine Learning: A Position Survey A. Kakas Loizos Michael 63 12 0 24 Oct 2020
Towards human-agent knowledge fusion (HAKF) in support of distributed coalition teams Dave Braines Federico Cerutti Marc Roig Vilamala Mani B. Srivastava Alun D. Preece G. Pearson 100 4 0 23 Oct 2020
Model Interpretability through the Lens of Computational ComplexityNeural Information Processing Systems (NeurIPS), 2020 Pablo Barceló Mikaël Monet Jorge A. Pérez Bernardo Subercaseaux 323 108 0 23 Oct 2020
Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New DomainsFindings (Findings), 2020 Eyal Shnarch Leshem Choshen Guy Moshkowich Noam Slonim R. Aharonov 270 13 0 19 Oct 2020
A Framework to Learn with InterpretationNeural Information Processing Systems (NeurIPS), 2020 Jayneel Parekh Pavlo Mozharovskyi Florence dÁlché-Buc AI4CE FAtt 286 32 0 19 Oct 2020
Squashing activation functions in benchmark tests: towards eXplainable Artificial Intelligence using continuous-valued logicKnowledge-Based Systems (KBS), 2020 Daniel Zeltner Benedikt Schmid G. Csiszár O. Csiszár AAML 55 16 0 17 Oct 2020
Physics-informed GANs for Coastal Flood Visualization Björn Lütjens B. Leshchinskiy C. Requena-Mesa F. Chishtie Natalia Díaz Rodríguez ... A. Piña Dava Newman Alexander Lavin Y. Gal Chedy Raïssi AI4CE 88 16 0 16 Oct 2020
Do's and Don'ts for Human and Digital Worker Integration Vinod Muthusamy Merve Unuvar Hagen Volzer Justin D. Weisz 112 3 0 15 Oct 2020
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines A. Konstantinov Lev V. Utkin FedML AI4CE 162 184 0 14 Oct 2020
Adaptive Deep Forest for Online Learning from Drifting Data Streams Lukasz Korycki Bartosz Krawczyk 74 5 0 14 Oct 2020
Integrating Intrinsic and Extrinsic Explainability: The Relevance of Understanding Neural Networks for Human-Robot Interaction Tom Weber S. Wermter 80 4 0 09 Oct 2020
Sickle-cell disease diagnosis support selecting the most appropriate machinelearning method: Towards a general and interpretable approach for cellmorphology analysis from microscopy images N. Petrovic Gabriel Moyà-Alcover Antoni Jaume-i-Capó Manuel González Hidalgo 99 41 0 09 Oct 2020
Association rules over time Iztok Fister Iztok Fister AI4TS 91 5 0 08 Oct 2020
Simplifying the explanation of deep neural networks with sufficient and necessary feature-sets: case of text classification Florentin Flambeau Jiechieu Kameni Norbert Tsopzé XAI FAtt MedIm 89 1 0 08 Oct 2020
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 288 30 0 04 Oct 2020
Explanation Ontology: A Model of Explanations for User-Centered AIInternational Workshop on the Semantic Web (SW), 2020 Shruthi Chari Oshani Seneviratne Daniel Gruen Morgan Foreman Amar K. Das D. McGuinness XAI 138 64 0 04 Oct 2020
Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature AggregationAAAI Conference on Artificial Intelligence (AAAI), 2020 S. Sattarzadeh M. Sudhakar Anthony Lem Shervin Mehryar K. N. Plataniotis Jongseong Jang Hyunwoo J. Kim Yeonjeong Jeong Sang-Min Lee Kyunghoon Bae FAtt XAI 135 35 0 01 Oct 2020
Explainable Deep Reinforcement Learning for UAV Autonomous Navigation Lei He Nabil Aouf Bifeng Song 134 13 0 30 Sep 2020
A Human-in-the-Loop Approach based on Explainability to Improve NTL Detection Bernat Coma-Puig J. Carmona 120 2 0 28 Sep 2020
A light-weight method to foster the (Grad)CAM interpretability and explainability of classification networksAutomation, Control, and Information Technology (ACIT), 2020 Alfred Schöttl FAtt 54 13 0 26 Sep 2020
A Diagnostic Study of Explainability Techniques for Text ClassificationConference on Empirical Methods in Natural Language Processing (EMNLP), 2020 Pepa Atanasova J. Simonsen Christina Lioma Isabelle Augenstein XAI FAtt 249 257 0 25 Sep 2020
What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural BackdoorsKnowledge Discovery and Data Mining (KDD), 2020 Yi-Shan Lin Wen-Chuan Lee Z. Berkay Celik XAI 187 105 0 22 Sep 2020
CURIE: A Cellular Automaton for Concept Drift DetectionData mining and knowledge discovery (DMKD), 2020 J. Lobo Javier Del Ser E. Osaba Nikolaos Perrakis Francisco Herrera AI4TS 98 7 0 21 Sep 2020
Principles and Practice of Explainable Machine LearningFrontiers in Big Data (Front. Big Data), 2020 Vaishak Belle I. Papantonis FaML 206 521 0 18 Sep 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 788 88 0 17 Sep 2020
MeLIME: Meaningful Local Explanation for Machine Learning Models T. Botari Frederik Hvilshoj Rafael Izbicki A. Carvalho AAML FAtt 183 19 0 12 Sep 2020
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance FusionApplied Sciences (Appl. Sci.), 2020 D. Rengasamy Benjamin Rothwell Grazziela Figueredo FaML FAtt 84 46 0 11 Sep 2020
Transparency and granularity in the SP Theory of Intelligence and its realisation in the SP Computer ModelStudies in Computational Intelligence (SCI), 2020 J. Wolff 197 5 0 07 Sep 2020
Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic DatasetIEEE Transactions on Artificial Intelligence (IEEE TAI), 2020 Erico Tjoa Cuntai Guan XAI FAtt 317 33 0 07 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 185 58 0 03 Sep 2020
Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems Jeremy E. Block Eric D. Ragan 116 8 0 02 Sep 2020
Face Image Quality Assessment: A Literature SurveyACM Computing Surveys (ACM CSUR), 2020 Torsten Schlett Christian Rathgeb O. Henniger Javier Galbally Julian Fierrez Christoph Busch CVBM 284 152 0 02 Sep 2020
Machine Reasoning Explainability K. Čyras R. Badrinath S. Mohalik A. Mujumdar Alexandros Nikou Alessandro Previti Vaishnavi Sundararajan Aneta Vulgarakis Feljan LRM 267 13 0 01 Sep 2020
Algorithmic Transparency with Strategic Users Qiaochu Wang Yan-ping Huang Stefanus Jasin P. Singh FaML FedML 95 28 0 21 Aug 2020