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Book Synopsis

XAI in Computer Vision.- Comparing XAI Explanations and Synthetic Data Augmentation Strategies in Neuroimaging AI.- Superpixel Correlation for Explainable Image Classification.- On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs.- Explaining Vision GNNs: A Semantic and Visual Analysis of Graph-based Image Classification.- Counterfactuals in XAI.- HalCECE: A Framework for Explainable Hallucination Detection through Conceptual Counterfactuals in Image Captioning.- Diffusion Counterfactuals for Image Regressors.- Mitigating Text Toxicity with Counterfactual Generation.- Guiding LLMs to Generate High-Fidelity and High-Quality Counterfactual Explanations for Text Classification.- Exploring Ensemble Strategies for Graph Counterfactual Explanations.- Explainable Sequential Decision Making.- Leveraging XAI Techniques for Context-Aware Energy Consumption Forecasting.- ConformaSegment: A Conformal Prediction-Based, Uncertainty-Aware, and Model-Agnostic Explainability Framework for Time-Series Forecasting.- FLEXtime: Filterbank Learning to Explain Time Series.- From Text to Space: Mapping Abstract Spatial Models in LLMs during a Grid-World Navigation Task.- Class-Dependent Perturbation Effects in Evaluating Time Series Attributions.- Explainable AI in Finance & Legal Frameworks for XAI Technologies.- XAI In Fraud Detection: A Causal Perspective.- Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations.- Legal Requirements, Trust Issues and Engineering Challenges - a Multi-Disciplinary Case for User-Specific Explainability.- Explainable Fairness in Mortgage Lending.- Cyber Risk Management with Time Varying Artificial Intelligence Models.

Explainable Artificial Intelligence

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A Paperback by Riccardo Guidotti

5 in stock


    View other formats and editions of Explainable Artificial Intelligence by Riccardo Guidotti

    Publisher: Springer
    Publication Date: 11/11/2025
    ISBN13: 9783032083296, 978-3032083296
    ISBN10: 303208329X

    Description

    Book Synopsis

    XAI in Computer Vision.- Comparing XAI Explanations and Synthetic Data Augmentation Strategies in Neuroimaging AI.- Superpixel Correlation for Explainable Image Classification.- On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs.- Explaining Vision GNNs: A Semantic and Visual Analysis of Graph-based Image Classification.- Counterfactuals in XAI.- HalCECE: A Framework for Explainable Hallucination Detection through Conceptual Counterfactuals in Image Captioning.- Diffusion Counterfactuals for Image Regressors.- Mitigating Text Toxicity with Counterfactual Generation.- Guiding LLMs to Generate High-Fidelity and High-Quality Counterfactual Explanations for Text Classification.- Exploring Ensemble Strategies for Graph Counterfactual Explanations.- Explainable Sequential Decision Making.- Leveraging XAI Techniques for Context-Aware Energy Consumption Forecasting.- ConformaSegment: A Conformal Prediction-Based, Uncertainty-Aware, and Model-Agnostic Explainability Framework for Time-Series Forecasting.- FLEXtime: Filterbank Learning to Explain Time Series.- From Text to Space: Mapping Abstract Spatial Models in LLMs during a Grid-World Navigation Task.- Class-Dependent Perturbation Effects in Evaluating Time Series Attributions.- Explainable AI in Finance & Legal Frameworks for XAI Technologies.- XAI In Fraud Detection: A Causal Perspective.- Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations.- Legal Requirements, Trust Issues and Engineering Challenges - a Multi-Disciplinary Case for User-Specific Explainability.- Explainable Fairness in Mortgage Lending.- Cyber Risk Management with Time Varying Artificial Intelligence Models.

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