Explainable Artificial Intelligence -

Explainable Artificial Intelligence

First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part III

Luca Longo (Herausgeber)

Buch | Softcover
XVII, 540 Seiten
2023 | 1st ed. 2023
Springer International Publishing (Verlag)
978-3-031-44069-4 (ISBN)
139,09 inkl. MwSt
This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. 
The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: 
Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine.
Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems.
Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.

xAI for time series and Natural Language Processing.- Human-centered explanations and xAI for Trustworthy and Responsible AI.- Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.

Erscheinungsdatum
Reihe/Serie Communications in Computer and Information Science
Zusatzinfo XVII, 540 p. 225 illus., 186 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 848 g
Themenwelt Mathematik / Informatik Informatik Netzwerke
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte argumentative-based approaches for explanations • Artificial Intelligence • causal inference & explanations • convolutional neural networks • decomposition of neural network-based models for XAI • explainability • interpretable machine learning • natural language processing for explanations • Neural networks • reinforcement learning for enhancing XAI
ISBN-10 3-031-44069-2 / 3031440692
ISBN-13 978-3-031-44069-4 / 9783031440694
Zustand Neuware
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