| 书目名称 | Geometric Structures of Statistical Physics, Information Geometry, and Learning | | 副标题 | SPIGL‘20, Les Houche | | 编辑 | Frédéric Barbaresco,Frank Nielsen | | 视频video | | | 概述 | Provides new geometric foundations of inference in machine learning based on statistical physics.Deepens mathematical physics models with new insights from statistical machine learning.Combines numeri | | 丛书名称 | Springer Proceedings in Mathematics & Statistics | | 图书封面 |  | | 描述 | .Machine learning and artificial intelligence increasingly use methodological tools rooted in statistical physics. Conversely, limitations and pitfalls encountered in AI question the very foundations of statistical physics. This interplay between AI and statistical physics has been attested since the birth of AI, and principles underpinning statistical physics can shed new light on the conceptual basis of AI. During the last fifty years, statistical physics has been investigated through new geometric structures allowing covariant formalization of the thermodynamics. Inference methods in machine learning have begun to adapt these new geometric structures to process data in more abstract representation spaces..This volume collects selected contributions on the interplay of statistical physics and artificial intelligence. The aim is to provide a constructive dialogue around a common foundation to allow the establishment of new principles and laws governing these two disciplines in a unified manner. The contributions were presented at the workshop on the Joint Structures and Common Foundation of Statistical Physics, Information Geometry and Inference for Learning which was held in Les | | 出版日期 | Conference proceedings 2021 | | 关键词 | Conference Proceedings; Statistical inference; Geometric mechanics; Lie group machine learning; Informat | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-77957-3 | | isbn_softcover | 978-3-030-77959-7 | | isbn_ebook | 978-3-030-77957-3Series ISSN 2194-1009 Series E-ISSN 2194-1017 | | issn_series | 2194-1009 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:15:18
