Information Theory and the Embedding Problem for Riemannian Manifolds

被引：2

作者：

Menon, Govind ^{[1
]}

机构：

[1] Brown Univ, Div Appl Math, Providence, RI 02912 USA

来源：

GEOMETRIC SCIENCE OF INFORMATION (GSI 2021) | 2021年 / 12829卷

基金：

美国国家科学基金会;

关键词：

Geometric information theory; Embedding theorems;

D O I：

10.1007/978-3-030-80209-7_65

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper provides an introduction to an information theoretic formulation of the embedding problem for Riemannian manifolds developed by the author. The main new construct is a stochastic relaxation scheme for embedding problems and hard constraint systems. This scheme is introduced with examples and context.

引用

页码：605 / 612

页数：8

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