logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Geometric And Topological Inference Boissonnat Jeandaniel Chazal

  • SKU: BELL-7235312
Geometric And Topological Inference Boissonnat Jeandaniel Chazal
$ 31.00 $ 45.00 (-31%)

4.8

64 reviews

Geometric And Topological Inference Boissonnat Jeandaniel Chazal instant download after payment.

Publisher: Cambridge University Press
File Extension: PDF
File size: 4.94 MB
Pages: 247
Author: Boissonnat, Jean-Daniel; Chazal, Frédéric; Yvinec, Mariette
Language: English
Year: 2018

Product desciption

Geometric And Topological Inference Boissonnat Jeandaniel Chazal by Boissonnat, Jean-daniel; Chazal, Frédéric; Yvinec, Mariette instant download after payment.

Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

Related Products