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Evaluation Metrics in Explainable Artificial Intelligence (XAI)

Advanced Research in Technologies, Information, Innovation and Sustainability, p.401-413

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The Tower of Babel in Explainable Artificial Intelligence (XAI)

Machine Learning and Knowledge Extraction, 2023, Vol.14065, p.65-81

2023

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Beyond Prediction Similarity: ShapGAP for Evaluating Faithful Surrogate Models in XAI

Explainable Artificial Intelligence, p.160-173

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A Comprehensive Survey of Explainable Artificial Intelligence (XAI) Methods: Exploring Transparency and Interpretability

Web Information Systems Engineering – WISE 2023, p.915-925

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Transparency and Interpretability for Learned Representations of Artificial Neural Networks

Meyes, Richard

1st Edition 2022, 2022

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Survey of Explainable Machine Learning with Visual and Granular Methods Beyond Quasi-Explanations

Interpretable Artificial Intelligence: A Perspective of Granular Computing, 2021, Vol.937, p.217-267

2021

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HIVE: Evaluating the Human Interpretability of Visual Explanations

Computer Vision - ECCV 2022, 2022, Vol.13672, p.280-298

2022

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Explainable Artificial Intelligence: Concepts and Current Progression

Explainable Edge AI: A Futuristic Computing Perspective, 2023, Vol.1072, p.1-17

2023

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Evaluating Self-attention Interpretability Through Human-Grounded Experimental Protocol

Explainable Artificial Intelligence, 2023, Vol.1903, p.26-46

2023

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Self-explaining AI as an Alternative to Interpretable AI

Artificial General Intelligence, 2020, Vol.12177, p.95-106

2020

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Harmonizing Feature Attributions Across Deep Learning Architectures: Enhancing Interpretability and Consistency

KI 2023: Advances in Artificial Intelligence, 2023, Vol.14236, p.90-97

2023

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X-ELM: A Fast Explainability Approach for Extreme Learning Machines

Advances in Computational Intelligence, p.411-422

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Explainability for Clustering Models

Soft Computing in Data Science, p.3-17

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Explainable Deep Learning-Based Solar Flare Prediction with Post Hoc Attention for Operational Forecasting

Discovery Science, p.567-581

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Evaluation of XAI Models for Interpretation of Deep Learning Techniques’ Results in Automated Plant Disease Diagnosis

Trends in Sustainable Smart Cities and Territories, p.417-428

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Post-hoc Explainable Reinforcement Learning Using Probabilistic Graphical Models

Advanced Computing, p.362-376

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Explainable Artificial Intelligence (XAI): Conception, Visualization and Assessment Approaches Towards Amenable XAI

Explainable Edge AI: A Futuristic Computing Perspective, 2022, Vol.1072, p.35-51

2022

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XAI—An Approach for Understanding Decisions Made by Neural Network

Recent Trends in Communication and Intelligent Systems, 2021, p.155-165

2021

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Survey of Explainable AI Techniques: A Case Study of Healthcare

ICT Systems and Sustainability, 2023, Vol.765, p.335-346

2023

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Explainable Machine Learning for Identifying Malicious Profiles in Online Social Networks

Artificial Intelligence and Smart Environment, 2023, Vol.635, p.537-545

2023

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Common Pitfalls When Explaining AI and Why Mechanistic Explanation Is a Hard Problem

Proceedings of Sixth International Congress on Information and Communication Technology, 2021, Vol.235, p.401-408

2021

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Ethnography as Data Science

Social Data Science Xennials, 2020, p.73-90

Campagnolo, Gian Marco

2020

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Explainable AI for the Operating Theater

Digital Surgery, 2020, p.339-350

Atallah, Sam

2020

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A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, p.3-15

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Post-hoc Counterfactual Generation with Supervised Autoencoder

Machine Learning and Principles and Practice of Knowledge Discovery in Databases, p.105-114

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Evaluation Metrics in Explainable Artificial Intelligence (XAI)

The Tower of Babel in Explainable Artificial Intelligence (XAI)

Beyond Prediction Similarity: ShapGAP for Evaluating Faithful Surrogate Models in XAI

A Comprehensive Survey of Explainable Artificial Intelligence (XAI) Methods: Exploring Transparency and Interpretability

Transparency and Interpretability for Learned Representations of Artificial Neural Networks

Survey of Explainable Machine Learning with Visual and Granular Methods Beyond Quasi-Explanations

HIVE: Evaluating the Human Interpretability of Visual Explanations

Explainable Artificial Intelligence: Concepts and Current Progression

Evaluating Self-attention Interpretability Through Human-Grounded Experimental Protocol

Self-explaining AI as an Alternative to Interpretable AI

Harmonizing Feature Attributions Across Deep Learning Architectures: Enhancing Interpretability and Consistency

X-ELM: A Fast Explainability Approach for Extreme Learning Machines

Explainability for Clustering Models

Explainable Deep Learning-Based Solar Flare Prediction with Post Hoc Attention for Operational Forecasting

Evaluation of XAI Models for Interpretation of Deep Learning Techniques’ Results in Automated Plant Disease Diagnosis

Post-hoc Explainable Reinforcement Learning Using Probabilistic Graphical Models

Explainable Artificial Intelligence (XAI): Conception, Visualization and Assessment Approaches Towards Amenable XAI

XAI—An Approach for Understanding Decisions Made by Neural Network

Survey of Explainable AI Techniques: A Case Study of Healthcare

Explainable Machine Learning for Identifying Malicious Profiles in Online Social Networks

Common Pitfalls When Explaining AI and Why Mechanistic Explanation Is a Hard Problem

Ethnography as Data Science

Explainable AI for the Operating Theater

A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field

Post-hoc Counterfactual Generation with Supervised Autoencoder

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