Interpretable artificial intelligence : a perspective of granular computing / Witold Pedrycz, Shyi-Ming Chen, editors.

Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring
Use of Visual Analytics (VA) in Explainable Artificial Intelligence(XAI): A Framework of Information Granules
Visualizing the Behavior of Convolutional Neural Networks for Time Series Forecasting
Beyond Deep Event Prediction: Deep Event Understanding Based on Explainable Artificial Intelligence
Interpretation of SVM to Build an Explainable AI via Granular Computing
Factual and Counterfactual Explanation of Fuzzy Information Granules
Transparency and Granularity in the SP Theory of Intelligence and Its Realisation in the SP Computer Model
Survey of Explainable Machine Learning with Visual and Granular Methods Beyond Quasi-Explanations
MiBeX: Malware-Inserted Benign Datasets for Explainable Machine Learning
Designing Explainable Text Classification Pipelines: Insights from IT Ticket Complexity Prediction Case Study
A Granular Computing Approach to Provide Transparency of Intelligent Systems for Criminal Investigations
RYEL System: A Novel Method for Capturing and Represent Knowledge in a Legal Domain Using Explainable Artificial Intelligence (XAI) and Granular Computing (GrC)
A Generative Model Based Approach for Zero-Shot Breast Cancer Segmentation Explaining Pixels' Contribution to the Model's Prediction.