Ubiquitous Laplacian: An Introduction To Numerical Pdes With Applications In Data Science

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Rongjie Lai (Prudue University, Usa) Xiangxiong Zhang (Purdue University, Usa)

Ubiquitous Laplacian

Name: Ubiquitous Laplacian
Price: 234.85 AUD
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ISBN: 9789819814534

An Introduction To Numerical Pdes With Applications In Data Science

Rongjie Lai (Prudue University, Usa), Xiangxiong Zhang (Purdue University, Usa)

$293.95 $234.85

Hardback

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English

World Scientific Publishing Co Pte Ltd
28 June 2026

Differential calculus & equations; Mathematical physics

Series: Progress In Data Science

Summary
Details

This book is designed for graduate students in applied and computational mathematics and is also accessible to students in engineering and computer science. It serves as a textbook for an introductory graduate-level course on numerical methods for solving partial differential equations (PDEs), with a focus on the Laplacian operator — a fundamental and ubiquitous tool in scientific computing and data science.

A distinctive feature of the book is its emphasis on the connections between numerical PDEs and modern data science. It presents a broad scope of applications across computational mathematics, including image processing, optimal transport, point clouds, shape matching, and data processing.

The book is organized into two parts. The first part covers classical numerical methods for the Laplacian or Poisson equation on structured grids, including conventional topics such as finite difference and finite element methods. The second part focuses on the Laplace-Beltrami operator on surfaces approximated by triangular meshes, and discrete Laplacians for point cloud representations of manifolds.

Throughout, the book includes homework-level problems and research-oriented projects suitable for undergraduate, junior graduate, and research-training assignments.

By: Rongjie Lai (Prudue University Usa), Xiangxiong Zhang (Purdue University, Usa)
Imprint: World Scientific Publishing Co Pte Ltd
Country of Publication: Singapore
Volume: 2
ISBN: 9789819814534
ISBN 10: 9819814537
Series: Progress In Data Science
Pages: 300
Publication Date: 28 June 2026
Audience: Professional and scholarly , College/higher education , Undergraduate , Further / Higher Education
Format: Hardback
Publisher's Status: Postponed Indefinitley