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A Survey Of Methods For Explaining Black Box Models

6 February 2018

Papers citing "A Survey Of Methods For Explaining Black Box Models"

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Title
Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers Zunlei Feng Jiacong Hu Sai Wu Xiaotian Yu Mingli Song Xiuming Zhang 78 14 0 09 Dec 2021
Multi-objective Explanations of GNN Predictions Yifei Liu Chao Chen Yazheng Liu Xi Zhang Sihong Xie 67 13 0 29 Nov 2021
Explainable Deep Image Classifiers for Skin Lesion Diagnosis C. Metta Andrea Beretta Riccardo Guidotti Yuan Yin Patrick Gallinari S. Rinzivillo F. Giannotti 44 5 0 22 Nov 2021
Learning by Active Forgetting for Neural Networks Jian Peng Xian Sun Min Deng Chao Tao Bo Tang ... Guohua Wu Qing Zhu Yu Liu Tao R. Lin Haifeng Li CLL KELM AI4CE 79 3 0 21 Nov 2021
Ubi-SleepNet: Advanced Multimodal Fusion Techniques for Three-stage Sleep Classification Using Ubiquitous Sensing B. Zhai Yu Guan M. Catt Thomas Ploetz 84 6 0 19 Nov 2021
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 88 69 0 15 Nov 2021
Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data Yanou Ramon S. Matz R. Farrokhnia David Martens 51 19 0 12 Nov 2021
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities Waddah Saeed C. Omlin XAI 102 446 0 11 Nov 2021
EvoLearner: Learning Description Logics with Evolutionary Algorithms Stefan Heindorf Lukas Blübaum Nick Dusterhus Till Werner Varun Nandkumar Golani Caglar Demir A. N. Ngomo 66 22 0 08 Nov 2021
Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging Gusseppe Bravo Rocca Peini Liu Jordi Guitart Ajay Dholakia David Ellison Jeffrey Falkanger M. Hodak 39 6 0 04 Nov 2021
Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities O. Kuiper M. V. D. Berg Joost van den Burgt S. Leijnen 59 19 0 03 Nov 2021
Instructive artificial intelligence (AI) for human training, assistance, and explainability Nicholas Kantack Nina Cohen Nathan D. Bos Corey Lowman James Everett Timothy Endres 27 2 0 02 Nov 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 103 51 0 27 Oct 2021
A Survey on Methods and Metrics for the Assessment of Explainability under the Proposed AI Act Francesco Sovrano Salvatore Sapienza M. Palmirani F. Vitali 69 18 0 21 Oct 2021
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences Q. V. Liao R. Varshney 124 234 0 20 Oct 2021
A New Approach for Interpretability and Reliability in Clinical Risk Prediction: Acute Coronary Syndrome Scenario Francisco Valente J. Henriques Simão Paredes Teresa Rocha Paulo de Carvalho João Morais OOD 52 22 0 15 Oct 2021
Tree-based local explanations of machine learning model predictions, AraucanaXAI Enea Parimbelli G. Nicora Szymon Wilk W. Michalowski Riccardo Bellazzi 35 26 0 15 Oct 2021
Using Psychological Characteristics of Situations for Social Situation Comprehension in Support Agents Ilir Kola Catholijn M. Jonker M. Birna van Riemsdijk 29 6 0 15 Oct 2021
Logic Constraints to Feature Importances Nicola Picchiotti Marco Gori 45 0 0 13 Oct 2021
Clustering-Based Interpretation of Deep ReLU Network Nicola Picchiotti Marco Gori FAtt 20 0 0 13 Oct 2021
Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates Xiaochuang Han Yulia Tsvetkov TDI 102 31 0 07 Oct 2021
Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model Alexander Sieusahai Matthew J. Guzdial 71 13 0 07 Oct 2021
Unpacking the Black Box: Regulating Algorithmic Decisions Laura Blattner Scott Nelson Jann Spiess MLAU FaML 80 19 0 05 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 150 705 0 05 Oct 2021
Trustworthy AI: From Principles to Practices Yue Liu Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 213 383 0 04 Oct 2021
LEMON: Explainable Entity Matching Nils Barlaug FAtt AAML 62 9 0 01 Oct 2021
AIive: Interactive Visualization and Sonification of Neural Networks in Virtual Reality Zhuoyue Lyu Jiannan Li Bryan Wang 29 16 0 30 Sep 2021
Improved prediction rule ensembling through model-based data generation Benny Markovitch M. Fokkema 16 0 0 28 Sep 2021
Trustworthy AI and Robotics and the Implications for the AEC Industry: A Systematic Literature Review and Future Potentials Newsha Emaminejad Reza Akhavian 55 50 0 27 Sep 2021
Time Series Model Attribution Visualizations as Explanations U. Schlegel Daniel A. Keim TDI BDL FAtt AI4TS XAI 84 15 0 27 Sep 2021
Explainability Pitfalls: Beyond Dark Patterns in Explainable AI Upol Ehsan Mark O. Riedl XAI SILM 101 64 0 26 Sep 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 67 81 0 23 Sep 2021
IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications Rui Yuan S. A. Pourmousavi W. Soong Giang Nguyen Jon A. R. Liisberg 42 7 0 23 Sep 2021
$Weighted Conditional EL{^}bot Knowledge Bases with Integer Weights: an ASP Approach$ Weighted Conditional EL{^}bot Knowledge Bases with Integer Weights: an ASP Approach Laura Giordano Daniele Theseider Dupré 51 7 0 17 Sep 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations Hangzhi Guo T. Nguyen A. Yadav OffRL 59 16 0 15 Sep 2021
Comparing decision mining approaches with regard to the meaningfulness of their results Beate Scheibel Stefanie Rinderle-Ma 18 4 0 15 Sep 2021
AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML CML HAI 39 21 0 12 Sep 2021
How Can Subgroup Discovery Help AIOps? Youcef Remil 30 2 0 10 Sep 2021
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud Michaela Hardt Xiaoguang Chen Xiaoyi Cheng Michele Donini J. Gelman ... Muhammad Bilal Zafar Sanjiv Ranjan Das Kevin Haas Tyler Hill K. Kenthapadi ELM FaML 80 43 0 07 Sep 2021
Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms B. Wickramanayake Zhipeng He Chun Ouyang Catarina Moreira Yue Xu Renuka Sindhgatta 46 27 0 03 Sep 2021
Combining Transformers with Natural Language Explanations Federico Ruggeri Marco Lippi Paolo Torroni 67 1 0 02 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond Amir Feder Katherine A. Keith Emaad A. Manzoor Reid Pryzant Dhanya Sridhar ... Roi Reichart Margaret E. Roberts Brandon M Stewart Victor Veitch Diyi Yang CML 118 246 0 02 Sep 2021
Look Who's Talking: Interpretable Machine Learning for Assessing Italian SMEs Credit Default Lisa Crosato C. Liberati M. Repetto 41 1 0 31 Aug 2021
XAI Methods for Neural Time Series Classification: A Brief Review Ilija vSimić Vedran Sabol Eduardo E. Veas BDL AI4TS 50 13 0 18 Aug 2021
Identifying Biased Subgroups in Ranking and Classification Eliana Pastor Luca de Alfaro Elena Baralis CML 46 12 0 17 Aug 2021
Synthesizing Pareto-Optimal Interpretations for Black-Box Models Hazem Torfah Shetal Shah Supratik Chakraborty S. Akshay Sanjit A. Seshia 139 6 0 16 Aug 2021
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems Jakob Schoeffer Niklas Kuehl 51 26 0 14 Aug 2021
On the Explanatory Power of Decision Trees Gilles Audemard S. Bellart Louenas Bounia F. Koriche Jean-Marie Lagniez Pierre Marquis FAtt 41 11 0 11 Aug 2021
Attention-like feature explanation for tabular data A. Konstantinov Lev V. Utkin FAtt 114 5 0 10 Aug 2021
Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery Youcef Remil Anes Bendimerad Marc Plantevit C. Robardet Mehdi Kaytoue-Uberall 32 5 0 06 Aug 2021