A survey of methods for explaining black box models

Riccardo Guidotti; Anna Monreale; Salvatore Ruggieri; Franco Turini; Fosca Giannotti; Dino Pedreschi

doi:https://doi.org/10.1145/3236009

A survey of methods for explaining black box models

2019 · ISTI Open Portal · 4,992 citations · 6 from inside this corpus

Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Franco Turini, Fosca Giannotti, Dino Pedreschi

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Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Definitions, methods, and applications in interpretable machine learning→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→A survey of methods for explaining black box modelsLegacy edge — source detail unavailable
A survey of methods for explaining black box models→"Why Should I Trust You?"Legacy edge — source detail unavailable
A survey of methods for explaining black box models→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
A survey of methods for explaining black box models→Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…Legacy edge — source detail unavailable
A survey of methods for explaining black box models→Intelligible Models for HealthCareLegacy edge — source detail unavailable
A survey of methods for explaining black box models→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
"Why Should I Trust You?"→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…Legacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→"Why Should I Trust You?"Legacy edge — source detail unavailable
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Definitions, methods, and applications in interpretable machine learning→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Definitions, methods, and applications in interpretable machine learning→"Why Should I Trust You?"Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→"Why Should I Trust You?"Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…Legacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→"Why Should I Trust You?"Legacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
Explainable AI: A Review of Machine Learning Interpretability Methods→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Intelligible Models for HealthCareLegacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→"Why Should I Trust You?"Legacy edge — source detail unavailable
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explaining nonlinear classification decisions with deep Taylor decompositionLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→"Why Should I Trust You?"Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Towards A Rigorous Science of Interpretable Machine LearningLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explainable AI: A Review of Machine Learning Interpretability MethodsLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
"Why Should I Trust You?"	2016	16,210
Towards A Rigorous Science of Interpretable Machine Learning	2017	3,190
Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual C…	2014	1,838
Intelligible Models for HealthCare	2015	1,693
Explaining nonlinear classification decisions with deep Taylor decomposition	2016	1,413

What cites it, inside the corpus

Paper	Year	Cited
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…	2019	9,796
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)	2018	6,166
Explainable AI: A Review of Machine Learning Interpretability Methods	2020	2,907
Definitions, methods, and applications in interpretable machine learning	2019	2,161
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…	2023	1,679
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications	2021	1,424

Links

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Topics

Explainable Artificial Intelligence (XAI)	Computer Science
Adversarial Robustness in Machine Learning	Computer Science
Bayesian Modeling and Causal Inference	Computer Science

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supports6 author record(s) attached.
supports82 reference(s) recorded.
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supportsA title is present.

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