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Topological and Statistical Methods for Complex Data

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Cover of 'Topological and Statistical Methods for Complex Data'

Table of Contents

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    Book Overview
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    Chapter 1 A Distributed-Memory Algorithm for Connected Components Labeling of Simulation Data
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    Chapter 2 In-Situ Visualization in Computational Fluid Dynamics Using Open-Source tools: Integration of Catalyst into Code_Saturne
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    Chapter 3 Sublinear Algorithms for Extreme-Scale Data Analysis
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    Chapter 4 Optimal General Simplification of Scalar Fields on Surfaces
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    Chapter 5 Piecewise Polynomial Monotonic Interpolation of 2D Gridded Data
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    Chapter 6 Shape Analysis and Description Using Real Functions
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    Chapter 7 3D Symmetric Tensor Fields: What We Know and Where To Go Next
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    Chapter 8 A Comparison of Pareto Sets and Jacobi Sets
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    Chapter 9 Deformations Preserving Gauss Curvature
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    Chapter 10 Lyapunov Time for 2D Lagrangian Visualization
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    Chapter 11 Geometric Algebra for Vector Field Analysis and Visualization: Mathematical Settings, Overview and Applications
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    Chapter 12 Computing Accurate Morse-Smale Complexes from Gradient Vector Fields
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    Chapter 13 Exercises in High-Dimensional Sampling: Maximal Poisson-Disk Sampling and k -d Darts
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    Chapter 14 Realization of Regular Maps of Large Genus
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    Chapter 15 Polynomial-Time Amoeba Neighborhood Membership and Faster Localized Solving
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    Chapter 16 Slycat Ensemble Analysis of Electrical Circuit Simulations
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32 Mendeley
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Title
Topological and Statistical Methods for Complex Data
Published by
Springer Berlin Heidelberg, January 2015
DOI 10.1007/978-3-662-44900-4
ISBNs
978-3-66-244899-1, 978-3-66-244900-4
Editors

Bennett, Janine, Vivodtzev, Fabien, Pascucci, Valerio

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Canada 1 3%
Unknown 30 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Researcher 7 22%
Student > Bachelor 5 16%
Student > Master 4 13%
Professor 2 6%
Other 5 16%
Readers by discipline Count As %
Computer Science 8 25%
Mathematics 7 22%
Agricultural and Biological Sciences 4 13%
Engineering 3 9%
Physics and Astronomy 2 6%
Other 8 25%