Categorical and geometric methods in statistical, manifold, and machine learning

2025/05/06 by Hông Vân Lê, Lê, Hông Vân, Hà Quang Minh +5
Computer Science · Mathematics · Physics and Astronomy · #Category Theory (math.CT) #Differential Geometry (math.DG) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Statistical Mechanics and Entropy #Statistics Theory (math.ST) #Topological and Geometric Data Analysis

paper · pdf · doi:10.48550/arxiv.2505.03862

openalex publication_date 2025/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present and discuss applications of the category of probabilistic morphisms, initially developed in \citeLe2023, as well as some geometric methods to several classes of problems in statistical, machine and manifold learning which shall be, along with many other topics, considered in depth in the forthcoming book \citeLMPT2024.

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