Geometric Science of Information: 7th International Conference, Gsi 2025, Saint-Malo, France, October 29-31, 2025, Proceedings, Part II
暫譯: 資訊的幾何科學:第七屆國際會議 GSI 2025,法國聖馬洛,2025年10月29-31日,會議錄,第二部分

Nielsen, Frank, Barbaresco, Frédéric

  • 出版商: Springer
  • 出版日期: 2025-09-22
  • 售價: $3,380
  • 貴賓價: 9.5$3,211
  • 語言: 英文
  • 頁數: 444
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3032039207
  • ISBN-13: 9783032039200
  • 相關分類: 機率統計學 Probability-and-statistics
  • 海外代購書籍(需單獨結帳)

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商品描述

The 3-volume set LNCS 16033 - 16035 constitutes the proceedings of the 7th International Conference on Geometric Science of Information, GSI 2025, held in St. Malo, France, during October 2025. The main theme of GSI 2025 was: Geometric Structures of Statistical and Quantum Physics, Information Geometry, and Machine Learning: FROM CLASSICAL TO QUANTUM INFORMATION GEOMETRY.

The 124 full papers included in the proceedings were carefully reviewed and selected from 146 submissions. They were organized in topical sections as follows:

Part I: Geometric Learning and Differential Invariants on Homogeneous Spaces; Statistical Manifolds and Hessian information geometry; Applied Geometry-Informed Machine Learning; Geometric Green Learning on Groups and Quotient Spaces; Divergences in Statistics and Machine Learning;

Part II: Geometric Statistics; Computational Information Geometry and Divergences; Geometric Methods in Thermodynamics; Classical & Quantum Information, Geometry and Topology; Geometric Mechanics; Stochastic Geometric Dynamics;

Part III: New trends in Nonholonomic Systems; Learning of Dynamic Processes; Optimization and learning on manifolds; Neurogeometry; Lie Group in Learning Distributions & in Filters; A geometric approach to differential equations; Information Geometry, Delzant Toric Manifold & Integrable System.

商品描述(中文翻譯)

《LNCS 16033 - 16035》三卷本是第七屆國際資訊幾何科學會議(GSI 2025)的會議論文集,該會議於2025年10月在法國聖馬洛舉行。GSI 2025的主要主題為:統計與量子物理的幾何結構、資訊幾何及機器學習:從經典到量子資訊幾何。

會議論文集中包含的124篇完整論文是從146篇投稿中經過仔細審查和選擇的。這些論文按主題分為以下幾個部分:

第一部分:均質空間上的幾何學習與微分不變量;統計流形與Hessian資訊幾何;應用幾何驅動的機器學習;群與商空間上的幾何綠色學習;統計與機器學習中的散度;

第二部分:幾何統計;計算資訊幾何與散度;熱力學中的幾何方法;經典與量子資訊、幾何與拓撲;幾何力學;隨機幾何動力學;

第三部分:非完整系統的新趨勢;動態過程的學習;流形上的優化與學習;神經幾何;學習分佈與濾波器中的李群;微分方程的幾何方法;資訊幾何、Delzant錐流形與可積系統。