xxAI - Beyond Explainable AI International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers

dc.contributor.authorAndreas Holzinger
dc.contributor.authorRandy Goebel
dc.contributor.authorRuth Fong
dc.contributor.authorTaesup Moon
dc.contributor.authorKlaus-Robert Müller
dc.contributor.authorWojciech Samek
dc.date.accessioned2026-05-07T21:20:56Z
dc.date.available2026-05-07T21:20:56Z
dc.date.issued2022
dc.descriptionLibro electrónico
dc.description.abstractThis is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans.
dc.identifier.isbn978-3-319-69623-1165
dc.identifier.otherhttps://doi.org/10.1007/978-3-031-04083-2
dc.identifier.urihttps://link.springer.com/openurl?genre=book&isbn=978-3-031-04083-2
dc.identifier.urihttp://bibliovirtual.umar.mx:4000/handle/123456789/2475
dc.language.isoen_US
dc.publisherSpringer International Publishing
dc.titlexxAI - Beyond Explainable AI International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers
dc.typeBook
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person.jobTitletrabajo

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