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Krishna Garikipati
Data-driven Modelling and Scientific Machine Learning in Continuum Physics

This monograph takes the reader through recent advances in data-driven methods and machine learning for problems in science-specifically in continuum physics. It develops the foundations and details a num…

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Andrea Bellavia
Statistical Methods for Environmental Mixtures

This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework. En…

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Stochastic Geometry: Percolation, Tesselations, Gaussian Fields and Point Processes

An Introduction to Russo-Seymour-Welsh Theory.- 2. Random Tessellations - An Overview of Models.- 3. Gaussian Fields through Geometrical Properties.- 4. Complex Gaussian Zeros and Eigenvalues.- 5. Point P…

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Methodological and Applied Statistics and Demography III

This book of peer-reviewed short papers on methodological and applied statistics and demography is the third of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024),…

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Nan Chen
Stochastic Methods for Modeling and Predicting Complex Dynamical Systems

This second edition is an essential guide to understanding, modeling, and predicting complex dynamical systems using new methods with stochastic tools. Expanding upon the original book, the author covers …

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Gerhard Tutz
A Short Guide to Item Response Theory Models

Preface.- Introduction.- The Binary Rasch Model.- Extensions of the Rasch Model and Alternative Binary Models.- Ordinal Models.- Extended Ordinal Models Accounting for Response Styles.- The Thresholds Mod…

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Lajos Horváth, Gregory Rice
Change Point Analysis for Time Series

This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic the…

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Ronald W. Shonkwiler, Franklin Mendivil
Explorations in Monte Carlo Methods

Monte Carlo Methods are among the most used, and useful, computational tools available today. They provide efficient and practical algorithms to solve a wide range of scientific and engineering problems i…

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Sinho Chewi, Jonathan Niles-Weed, Philippe Rigollet
Statistical Optimal Transport

This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. It is primarily tailored for students and researcher…

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Sören Bartels
Numerical Mathematics 3x9

This book provides an introduction to methods for practically solving mathematical problems, such as solving systems of linear equations, determining eigenvalues, approximating and integrating functions, …

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More UK Success Stories in Industrial Mathematics

This volume highlights successful projects in which academic mathematicians in the United Kingdom got involved with solving problems in industry for which mathematics was essential. It contains a wide ran…

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Mircea D. Grigoriu
Numerical Methods for Extreme Responses of Dynamical Systems

This book constructs input finite dimensional (FD) models that are amendable for numerical calculations and provides accurate representations for responses of dynamical systems to these inputs, i.e., nume…

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Methodological and Applied Statistics and Demography II

This book of peer-reviewed short papers on methodological and applied statistics and demography is the second of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024)…

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Algorithms and Computational Theory for Engineering Applications

This book goes deeply into the world of algorithms and computational theory and its astounding influence on numerous engineering areas. The book's carefully chosen content highlights the most recent studi…

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Thomas W. Macfarland
Introduction to Data Science in Biostatistics

Introduction to Data Science in Biostatistics: Using R, the Tidyverse Ecosystem, and APIs defines and explores the term "data science" and discusses the many professional skills and competencies…

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Raymond J. Spiteri, Kyle Klenk
Extreme-Scale Computing

Part 1 - Extreme Scientific Computing Software Management.- Chapter 1 Linux Command Line.- Chapter 2: Version Control and Repositories.- Chapter 3: Building Software.- Part 2 - Programming Patterns and Mo…

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David Levanony, Peter E. Caines
Stochastic Lagrangian Adaptation

This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimatio…

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Numerical Geometry, Grid Generation and Scientific Computing

This volume presents a selection of papers presented at the 11th International Conference on Numerical Geometry, Grid Generation, and Scientific Computing held December 12-14, 2022 in memory of Sergei Ale…

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Kenneth J. Berry, Janis E. Johnston
Statistical Methods: Connections, Equivalencies, and Relationships

The primary purpose of this book is to introduce the reader to a wide variety of interesting and useful connections, relationships, and equivalencies between and among conventional and permutation statist…

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Hang Lee
Foundations of Applied Statistical Methods

This book covers methods of applied statistics for researchers who design and conduct experiments, perform statistical inference, and write technical reports. These research activities rely on an adequate…

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