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Explainable Artificial Intelligence

Second World Conference, xAI 2024, Valletta, Malta, July 17-19, 2024, Proceedings, Part I
BuchKartoniert, Paperback
494 Seiten
Englisch
Springererschienen am10.07.20242024
This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR139,09
BuchKartoniert, Paperback
EUR139,09
BuchKartoniert, Paperback
EUR90,94
BuchKartoniert, Paperback
EUR85,59
BuchKartoniert, Paperback
EUR85,59
BuchKartoniert, Paperback
EUR90,94
BuchKartoniert, Paperback
EUR85,59
E-BookPDF1 - PDF WatermarkE-Book
EUR149,79

Produkt

KlappentextThis four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024.
Details
ISBN/GTIN978-3-031-63786-5
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2024
Erscheinungsdatum10.07.2024
Auflage2024
ReiheCommunications in Computer and Information Science
Seiten494 Seiten
SpracheEnglisch
Gewicht768 g
IllustrationenXVII, 494 p. 143 illus., 137 illus. in color.
Artikel-Nr.56376468

Inhalt/Kritik

Inhaltsverzeichnis
.- Intrinsically interpretable XAI and concept-based global explainability..- Seeking Interpretability and Explainability in Binary Activated Neural Networks..- Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges..- Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model..- Revisiting FunnyBirds evaluation framework for prototypical parts networks..- CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision Models..- Unveiling the Anatomy of Adversarial Attacks: Concept-based XAI Dissection of CNNs..- AutoCL: AutoML for Concept Learning..- Locally Testing Model Detections for Semantic Global Concepts..- Knowledge graphs for empirical concept retrieval..- Global Concept Explanations for Graphs by Contrastive Learning..- Generative explainable AI and verifiability..- Augmenting XAI with LLMs: A Case Study in Banking Marketing Recommendation..- Generative Inpainting for Shapley-Value-Based Anomaly Explanation..- Challenges and Opportunities in Text Generation Explainability..- NoNE Found: Explaining the Output of Sequence-to-Sequence Models when No Named Entity is Recognized..- Notion, metrics, evaluation and benchmarking for XAI..- Benchmarking Trust: A Metric for Trustworthy Machine Learning..- Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI..- Conditional Calibrated Explanations: Finding a Path between Bias and Uncertainty..- Meta-evaluating stability measures: MAX-Sensitivity & AVG-Senstivity..- Xpression: A unifying metric to evaluate Explainability and Compression of AI models..- Evaluating Neighbor Explainability for Graph Neural Networks..- A Fresh Look at Sanity Checks for Saliency Maps..- Explainability, Quantified: Benchmarking XAI techniques..- BEExAI: Benchmark to Evaluate Explainable AI..- Associative Interpretability of Hidden Semantics with Contrastiveness Operators in Face Classification tasks.mehr

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