Topological Data Analysis: The Abel Symposium 2018, Baas Nils A., Carlsson Gunnar E., Quick Gereon

Автор: Baas Nils A., Carlsson Gunnar E., Quick Gereon
Название: Topological Data Analysis: The Abel Symposium 2018
ISBN: 3030434079 ISBN-13(EAN): 9783030434076
Издательство: Springer
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Цена: 186330.00 T
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Описание: This book gathers the proceedings of the 2018 Abel Symposium, which was held in Geiranger, Norway, on June 4-8, 2018. This volume presents papers on various research directions, notably including applications in neuroscience, materials science, cancer biology, and immune response.

Автор: Frigessi Arnoldo, Buhlmann Peter, Glad Ingrid
Название: Statistical Analysis for High-Dimensional Data: The Abel Symposium 2014
ISBN: 3319800736 ISBN-13(EAN): 9783319800738
Издательство: Springer
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Цена: 139750.00 T
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Описание:

Some Themes in High-Dimensional Statistics: A. Frigessi et al.- Laplace Appoximation in High-Dimensional Bayesian Regression: R. Barber, M. Drton et al.- Preselection in Lasso-Type Analysis for Ultra-High Dimensional Genomic Exploration: L.C. Bergersen, I. Glad et al.- Spectral Clustering and Block Models: a Review and a new Algorithm: S. Bhattacharyya et al.- Bayesian Hierarchical Mixture Models: L. Bottelo et al.- iBATCGH; Integrative Bayesian Analysis of Transcriptomic and CGH Data: Cassese, M. Vannucci et al.- Models of Random Sparse Eigenmatrices and Bayesian Analysis of Multivariate Structure: A.J. Cron, M. West.- Combining Single and Paired End RNA-seq Data for Differential Expression Analysis: F. Feng, T.Speed et al.- An Imputation Method for Estimation the Learning Curve in Classification Problems: E. Laber et al.- Baysian Feature Allocation Models for Tumor Heterogeneity: J. Lee, P. Mueller et al.- Bayesian Penalty Mixing: The Case of a Non-Separable Penalty: V. Rockova et al.- Confidence Intervals for Maximin Effects in Inhomogeneous Large Scale Data: D. Rothenhausler et al.- Chisquare Confidence Sets in High-Dimensional Regression: S. van de Geer et al.

Автор: Ceravolo Paolo, Van Keulen Maurice, Gуmez-Lуpez Marнa Teresa
Название: Data-Driven Process Discovery and Analysis: 8th Ifip Wg 2.6 International Symposium, Simpda 2018, Seville, Spain, December 13-14, 2018, and 9th Intern
ISBN: 3030466329 ISBN-13(EAN): 9783030466329
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book constitutes revised selected papers from the 8th and 9th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2018, held in Seville, Spain, on December 13-14, 2018, and SIMPDA 2019, held in Bled, Slovenia, on September 8, 2019.

Автор: Hsing Tailen
Название: Theoretical Foundations of Functional Data Analysis, with an
ISBN: 0470016914 ISBN-13(EAN): 9780470016916
Издательство: Wiley
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Цена: 69640.00 T
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Описание: ?? Provides a concise but rigorous account of the theoretical background of FDA. ?? Introduces topics in various areas of mathematics, probability and statistics from the perspective of FDA. ?? Presents a systematic exposition of the fundamental statistical issues in FDA.

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
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Цена: 84430.00 T
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Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.

Автор: Carr Hamish, Fujishiro Issei, Sadlo Filip
Название: Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications
ISBN: 3030430359 ISBN-13(EAN): 9783030430351
Издательство: Springer
Цена: 167700.00 T
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Описание: This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work.

Автор: Tierny Julien
Название: Topological Data Analysis for Scientific Visualization
ISBN: 3319715062 ISBN-13(EAN): 9783319715063
Издательство: Springer
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Цена: 130430.00 T
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Описание: 1. Introduction.- 2. Background: 2.1 Data representation.- 2.2 Topological abstractions.- 2.3 Algorithms and applications.- 3. Abstraction: 3.1 Efficient topological simplification of scalar fields.- 3.2 Efficient Reeb graph computation for volumetric meshes.- 4. Interaction: 4.1 Topological simplification of isosurfaces.- 4.2 Interactive editing of topological abstractions.- 5. Analysis: 5.1 Exploration of turbulent combustion simulations.- 5.2 Quantitative analysis of molecular interactions.- 6. Perspectives: 6.1 Emerging constraints.- 6.2 Emerging data types.- 7. Conclusion.

Автор: Pascucci
Название: Topological Methods in Data Analysis and Visualization
ISBN: 3642150136 ISBN-13(EAN): 9783642150135
Издательство: Springer
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Цена: 135090.00 T
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Описание: Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc. . The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field. This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on Topological Methods in Data Analysis and Visualization , held 2009 in Snowbird, Utah, US. The 2009 TopoInVis workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).

Автор: Pascucci Valerio, Tricoche Xavier, Hagen Hans
Название: Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications
ISBN: 3662506041 ISBN-13(EAN): 9783662506042
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Utah, US. It offers an important contribution to the field.

Автор: Hamish Carr; Christoph Garth; Tino Weinkauf
Название: Topological Methods in Data Analysis and Visualization IV
ISBN: 3319831100 ISBN-13(EAN): 9783319831107
Издательство: Springer
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Цена: 158380.00 T
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Автор: Tierny Julien
Название: Topological Data Analysis for Scientific Visualization
ISBN: 3319890794 ISBN-13(EAN): 9783319890791
Издательство: Springer
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Цена: 74530.00 T
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Описание: 1. Introduction.- 2. Background: 2.1 Data representation.- 2.2 Topological abstractions.- 2.3 Algorithms and applications.- 3. Abstraction: 3.1 Efficient topological simplification of scalar fields.- 3.2 Efficient Reeb graph computation for volumetric meshes.- 4. Interaction: 4.1 Topological simplification of isosurfaces.- 4.2 Interactive editing of topological abstractions.- 5. Analysis: 5.1 Exploration of turbulent combustion simulations.- 5.2 Quantitative analysis of molecular interactions.- 6. Perspectives: 6.1 Emerging constraints.- 6.2 Emerging data types.- 7. Conclusion.

Автор: Rabadan, Raul (columbia University, New York) Blumberg, Andrew J. (university Of Texas, Austin)
Название: Topological data analysis for genomics and evolution
ISBN: 1107159547 ISBN-13(EAN): 9781107159549
Издательство: Cambridge Academ
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Цена: 48570.00 T
Наличие на складе: Нет в наличии.
Описание: Algebraic topology is particularly suited for the analysis of high dimensional large data sets, including those in modern biology. The book introduces geometric and topological methods, including statistics, as well as applications to biology - including cancer genetics, single cell studies and reconstructing evolutionary relationships from genomic data.