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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
Explainable Multi-class Classification of the CAMH COVID-19 Mental Health Data Yuanzheng Hu Marina Sokolova 39 7 0 27 May 2021
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization Emilio Gamba B. Bogaerts Tias Guns LRM 97 7 0 25 May 2021
Argumentative XAI: A Survey Kristijonas vCyras Antonio Rago Emanuele Albini P. Baroni Francesca Toni 76 144 0 24 May 2021
On Explaining Random Forests with SAT Yacine Izza Sasha Rubin FAtt 123 75 0 21 May 2021
Yes We Care! -- Certification for Machine Learning Methods through the Care Label Framework K. Morik Helena Kotthaus Raphael Fischer Sascha Mucke Matthias Jakobs Nico Piatkowski Andrea Pauly Lukas Heppe Danny Heinrich 60 11 0 21 May 2021
Probabilistic Sufficient Explanations Eric Wang Pasha Khosravi Guy Van den Broeck XAI FAtt TPM 174 25 0 21 May 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 138 142 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 153 198 0 15 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 62 0 0 14 May 2021
Automating Data Science: Prospects and Challenges Tijl De Bie Luc de Raedt José Hernández-Orallo Holger H. Hoos Padhraic Smyth C. Williams 124 38 0 12 May 2021
Towards Dynamic Feature Selection with Attention to Assist Banking Customers in Establishing a New Business M. Edrisi 32 0 0 09 May 2021
Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inference Mokanarangan Thayaparan Marco Valentino Deborah Ferreira Julia Rozanova André Freitas 120 10 0 07 May 2021
Explainable Autonomous Robots: A Survey and Perspective Tatsuya Sakai Takayuki Nagai 67 68 0 06 May 2021
Explainable Artificial Intelligence for Human Decision-Support System in Medical Domain Samanta Knapic A. Malhi Rohit Saluja Kary Främling 24 102 0 05 May 2021
Rethinking Search: Making Domain Experts out of Dilettantes Donald Metzler Yi Tay Dara Bahri Marc Najork LRM 103 47 0 05 May 2021
Learning by Design: Structuring and Documenting the Human Choices in Machine Learning Development Simon Enni Ira Assent 24 3 0 03 May 2021
Interpretable Semantic Photo Geolocation Jonas Theiner Eric Müller-Budack Ralph Ewerth 48 30 0 30 Apr 2021
TrustyAI Explainability Toolkit Rob Geada Tommaso Teofili Rui Vieira Rebecca Whitworth Daniele Zonca 57 2 0 26 Apr 2021
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case Natalia Díaz Rodríguez Alberto Lamas Jules Sanchez Gianni Franchi Ivan Donadello Siham Tabik David Filliat P. Cruz Rosana Montes Francisco Herrera 136 78 0 24 Apr 2021
Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities Julia Rosenzweig Joachim Sicking Sebastian Houben Michael Mock Maram Akila AAML 99 3 0 22 Apr 2021
SurvNAM: The machine learning survival model explanation Lev V. Utkin Egor D. Satyukov A. Konstantinov AAML FAtt 93 30 0 18 Apr 2021
Faithful and Plausible Explanations of Medical Code Predictions Zach Wood-Doughty Isabel Cachola Mark Dredze 14 2 0 16 Apr 2021
LEx: A Framework for Operationalising Layers of Machine Learning Explanations Ronal Singh Upol Ehsan M. Cheong Mark O. Riedl Tim Miller 32 4 0 15 Apr 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations Dieter Brughmans Pieter Leyman David Martens 81 65 0 15 Apr 2021
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches Dmitry Kazhdan B. Dimanov Helena Andrés-Terré M. Jamnik Pietro Lio Adrian Weller CoGe DRL 48 23 0 14 Apr 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE) M. Virgolin A. D. Lorenzo Francesca Randone Eric Medvet M. Wahde 101 31 0 13 Apr 2021
Understanding Prediction Discrepancies in Machine Learning Classifiers X. Renard Thibault Laugel Marcin Detyniecki FaML 84 13 0 12 Apr 2021
Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks Hanjie Chen Song Feng Jatin Ganhotra H. Wan Chulaka Gunasekara Sachindra Joshi Yangfeng Ji 73 18 0 09 Apr 2021
Question-Driven Design Process for Explainable AI User Experiences Q. V. Liao Milena Pribić Jaesik Han Sarah Miller Daby M. Sow 126 54 0 08 Apr 2021
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features Suryabhan Singh Hada Miguel Á. Carreira-Perpiñán Arman Zharmagambetov 65 17 0 07 Apr 2021
White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks Meghna P. Ayyar J. Benois-Pineau A. Zemmari FAtt 34 17 0 06 Apr 2021
Contrastive Explanations for Explaining Model Adaptations André Artelt Fabian Hinder Valerie Vaquet Robert Feldhans Barbara Hammer 77 4 0 06 Apr 2021
The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions Senthil Kumar Jagatheesaperumal Mohamed Rahouti Kashif Ahmad Ala I. Al-Fuqaha Mohsen Guizani AI4CE 74 19 0 06 Apr 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 85 46 0 06 Apr 2021
Model Compression for Dynamic Forecast Combination Vítor Cerqueira Luís Torgo Carlos Soares Albert Bifet AI4TS AI4CE 27 4 0 05 Apr 2021
Distributed Banach-Picard Iteration for Locally Contractive Maps Francisco Andrade Mário A. T. Figueiredo J. Xavier 51 2 0 31 Mar 2021
Data in context: How digital transformation can support human reasoning in cyber-physical production systems Romy Müller F. Kessler David W. Humphrey Julian Rahm 20 7 0 31 Mar 2021
Channel-Based Attention for LCC Using Sentinel-2 Time Series Hermann Courteille A. Benoît N. Méger A. Atto Dino Ienco AI4TS 29 1 0 31 Mar 2021
A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms Ana Lucic Madhulika Srikumar Umang Bhatt Alice Xiang Ankur Taly Q. V. Liao Maarten de Rijke 45 5 0 27 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 105 110 0 22 Mar 2021
Weakly Supervised Recovery of Semantic Attributes Ameen Ali Tomer Galanti Evgeniy Zheltonozhskiy Chaim Baskin Lior Wolf 49 0 0 22 Mar 2021
Detecting Racial Bias in Jury Selection Jack Dunn Ying Daisy Zhuo 55 1 0 22 Mar 2021
Local Interpretations for Explainable Natural Language Processing: A Survey Siwen Luo Hamish Ivison S. Han Josiah Poon MILM 120 51 0 20 Mar 2021
Refining Language Models with Compositional Explanations Huihan Yao Ying Chen Qinyuan Ye Xisen Jin Xiang Ren 89 36 0 18 Mar 2021
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones Andrew P. Creagh F. Lipsmeier M. Lindemann M. D. Vos 105 17 0 16 Mar 2021
Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset Adrianna Janik J. Dodd Georgiana Ifrim Kris Sankaran Kathleen M. Curran 69 27 0 15 Mar 2021
Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts Ayoub El Qadi Natalia Díaz Rodríguez M. Trocan Thomas Frossard 17 6 0 15 Mar 2021
A conditional, a fuzzy and a probabilistic interpretation of self-organising maps Laura Giordano Valentina Gliozzi Daniele Theseider Dupré AI4CE 68 23 0 11 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 74 31 0 10 Mar 2021
Interpretable Machines: Constructing Valid Prediction Intervals with Random Forests Burim Ramosaj 26 2 0 09 Mar 2021