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Book Sections Year : 2022

Topological Data Analysis

Abstract

It has been observed since a long time that data are often carrying interesting topological and geometric structures. Characterizing such structures and providing efficient tools to infer and exploit them is a challenging problem that asks for new mathematics and that is motivated by a real need from applications. This paper is an introduction to Topological Data Analysis (), a new field that emerged during the last two decades with the objective of understanding and exploiting the topological structure of modern and complex data. The paper surveys some important mathematical and algorithmic developments in as well as software solutions that are currently used to address various applied and industrial problems.
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Dates and versions

hal-03813929 , version 1 (13-10-2022)

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Jean-Daniel Boissonnat, Frédéric Chazal, Bertrand Michel. Topological Data Analysis. Novel Mathematics Inspired by Industrial Challenges, 38, Springer International Publishing, pp.247-269, 2022, Mathematics in Industry, ⟨10.1007/978-3-030-96173-2_9⟩. ⟨hal-03813929⟩
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