Society for Industrial and Applied Mathematics: Applied Mathematics Education
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Design of DelayBased Controllers for Linear TimeInvariant Systems
https://epubs.siam.org/doi/book/10.1137/1.9781611978148?af=R
Design of DelayBased Controllers for Linear TimeInvariant Systems. <br/> This book provides the mathematical foundations needed for designing practical controllers for linear timeinvariant systems. The authors accomplish this by incorporating intentional time delays into measurements with the goal of achieving anticipation capabilities, reduction in noise sensitivity, and a fast response. The benefits of these types of delaybased controllers have long been recognized, but designing them based on an analytical approach become possible only recently.
Design of DelayBased Controllers for Linear TimeInvariant Systems. <br/> This book provides the mathematical foundations needed for designing practical controllers for linear timeinvariant systems. The authors accomplish this by incorporating intentional time delays into measurements with the goal of achieving anticipation capabilities, reduction in noise sensitivity, and a fast response. The benefits of these types of delaybased controllers have long been recognized, but designing them based on an analytical approach become possible only recently. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/dc/2024/1.9781611978148/1.9781611978148/20240917/1.9781611978148.cover.jpg" alttext="cover image"/></p>
Design of DelayBased Controllers for Linear TimeInvariant Systems
doi:10.1137/1.9781611978148
Adrián Ramírez
Rifat Sipahi
Sabine Mondié
Rubén Garrido
Design of DelayBased Controllers for Linear TimeInvariant Systems
20240917T04:01:45Z
10.1137/1.9781611978148
https://epubs.siam.org/doi/book/10.1137/1.9781611978148?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Algorithmic Mathematics in Machine Learning
https://epubs.siam.org/doi/book/10.1137/1.9781611977882?af=R
Algorithmic Mathematics in Machine Learning. <br/> The story of machine learning is one of rigorous success. It is frequently employed by scientists and practitioners around the globe in various areas of application ranging from economics to chemistry, from medicine to engineering, from gaming to astronomy, and from speech processing to computer vision. While the remarkable success of machine learning methods speaks for itself, they are often applied in an ad hoc manner without much care for their mathematical foundation or for their algorithmic intricacies. Therefore, we decided to write this book. Our goal is to provide the necessary background on commonly used machine learning algorithms and to highlight important implementational and numerical details. The book is based on a wellreceived practical lab course, which we established within the mathematics studies course at the University of Bonn, Germany, in 2017. The course has been taught and successively enhanced each year since then.
Algorithmic Mathematics in Machine Learning. <br/> The story of machine learning is one of rigorous success. It is frequently employed by scientists and practitioners around the globe in various areas of application ranging from economics to chemistry, from medicine to engineering, from gaming to astronomy, and from speech processing to computer vision. While the remarkable success of machine learning methods speaks for itself, they are often applied in an ad hoc manner without much care for their mathematical foundation or for their algorithmic intricacies. Therefore, we decided to write this book. Our goal is to provide the necessary background on commonly used machine learning algorithms and to highlight important implementational and numerical details. The book is based on a wellreceived practical lab course, which we established within the mathematics studies course at the University of Bonn, Germany, in 2017. The course has been taught and successively enhanced each year since then. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/di/2024/1.9781611977882/1.9781611977882/20240325/1.9781611977882.cover.jpg" alttext="cover image"/></p>
Algorithmic Mathematics in Machine Learning
doi:10.1137/1.9781611977882
Bastian Bohn
Jochen Garcke
Michael Griebel
Algorithmic Mathematics in Machine Learning
20240325T09:13:41Z
10.1137/1.9781611977882
https://epubs.siam.org/doi/book/10.1137/1.9781611977882?af=R
© 2024 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Computational Discovery on Jupyter
https://epubs.siam.org/doi/book/10.1137/1.9781611977509?af=R
Computational Discovery on Jupyter. <br/>This is a different sort of book (indeed, we're a bit doubtful about calling it a “book,” even), intended for a different sort of course. The content is intended to be outside the normal mathematics curriculum. The book won't teach calculus or linear algebra, for example, although it will reinforce, support, and illuminate those subjects, which we imagine you will be taking eventually (possibly even concurrently). We assume only high school mathematics to start, although we get pretty deep pretty quickly. What does this mean? We assume that you have been exposed to algebra, matrices, functions, and basic calculus (informal limits, continuity, some rules for taking derivatives and antiderivatives). We assume no prior programming knowledge. We assume you've met with mathematical induction. What we mostly assume is that you're willing to take charge of your own learning. You should be prepared to actually do things as you read. There are activities to do, ranging from simple (with reports on what we did in the Reports section so you have more models of the process) to hard, namely projects that can be done by teams (and if you answer them, you could contribute a chapter to this book, maybe), and some actually open. If you answer one of those, you should publish a paper in a journal. Maple Transactions1 might be a good place.
Computational Discovery on Jupyter. <br/>This is a different sort of book (indeed, we're a bit doubtful about calling it a “book,” even), intended for a different sort of course. The content is intended to be outside the normal mathematics curriculum. The book won't teach calculus or linear algebra, for example, although it will reinforce, support, and illuminate those subjects, which we imagine you will be taking eventually (possibly even concurrently). We assume only high school mathematics to start, although we get pretty deep pretty quickly. What does this mean? We assume that you have been exposed to algebra, matrices, functions, and basic calculus (informal limits, continuity, some rules for taking derivatives and antiderivatives). We assume no prior programming knowledge. We assume you've met with mathematical induction. What we mostly assume is that you're willing to take charge of your own learning. You should be prepared to actually do things as you read. There are activities to do, ranging from simple (with reports on what we did in the Reports section so you have more models of the process) to hard, namely projects that can be done by teams (and if you answer them, you could contribute a chapter to this book, maybe), and some actually open. If you answer one of those, you should publish a paper in a journal. Maple Transactions1 might be a good place.<p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2023/1.9781611977509/1.9781611977509/20231107/1.9781611977509.cover.jpg" alttext="cover image"/></p>
Computational Discovery on Jupyter
doi:10.1137/1.9781611977509
Neil J. Calkin
Eunice Y. S. Chan
Robert M. Corless
Computational Discovery on Jupyter
20231107T07:45:38Z
10.1137/1.9781611977509
https://epubs.siam.org/doi/book/10.1137/1.9781611977509?af=R
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Math Modeling: Getting Started and Getting Solutions
https://epubs.siam.org/doi/book/10.1137/1.9781611973570?af=R
Math Modeling: Getting Started and Getting Solutions. <br/>
Math Modeling: Getting Started and Getting Solutions. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2014/1.9781611973570/1.9781611973570/20231006/1.9781611973570.cover.jpg" alttext="cover image"/></p>
Math Modeling: Getting Started and Getting Solutions
doi:10.1137/1.9781611973570
Math Modeling: Getting Started and Getting Solutions
20231006T08:36:52Z
10.1137/1.9781611973570
https://epubs.siam.org/doi/book/10.1137/1.9781611973570?af=R
© 2014 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Math Modeling: Computing and Communicating
https://epubs.siam.org/doi/book/10.1137/1.9781611975239?af=R
Math Modeling: Computing and Communicating. <br/>
Math Modeling: Computing and Communicating. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2018/1.9781611975239/1.9781611975239/20231006/1.9781611975239.cover.jpg" alttext="cover image"/></p>
Math Modeling: Computing and Communicating
doi:10.1137/1.9781611975239
Math Modeling: Computing and Communicating
20231006T08:36:12Z
10.1137/1.9781611975239
https://epubs.siam.org/doi/book/10.1137/1.9781611975239?af=R
© 2018 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

GAIMME — Guidelines for Assessment & Instruction in Mathematical Modeling Education
https://epubs.siam.org/doi/book/10.1137/1.9781611975741?af=R
GAIMME — Guidelines for Assessment &Instruction in Mathematical Modeling Education. <br/>
GAIMME — Guidelines for Assessment & Instruction in Mathematical Modeling Education. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2019/1.9781611975741/1.9781611975741/20231006/1.9781611975741.cover.jpg" alttext="cover image"/></p>
GAIMME — Guidelines for Assessment & Instruction in Mathematical Modeling Education
doi:10.1137/1.9781611975741
GAIMME — Guidelines for Assessment & Instruction in Mathematical Modeling Education
20231006T08:35:32Z
10.1137/1.9781611975741
https://epubs.siam.org/doi/book/10.1137/1.9781611975741?af=R
© 2019 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Careers in the Mathematical Sciences
https://epubs.siam.org/doi/book/10.1137/1.9781611977219?af=R
Careers in the Mathematical Sciences. <br/> Applied mathematics and computational and data science impact nearly every facet of our lives. In this guide, you will find answers to questions about careers in applied mathematics and computational and data science, and profiles of professionals working in a variety of environments for which a strong background in mathematics is necessary for success.
Careers in the Mathematical Sciences. <br/> Applied mathematics and computational and data science impact nearly every facet of our lives. In this guide, you will find answers to questions about careers in applied mathematics and computational and data science, and profiles of professionals working in a variety of environments for which a strong background in mathematics is necessary for success. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2022/1.9781611977219/1.9781611977219/20231006/1.9781611977219.cover.jpg" alttext="cover image"/></p>
Careers in the Mathematical Sciences
doi:10.1137/1.9781611977219
Careers in the Mathematical Sciences
20231006T08:34:52Z
10.1137/1.9781611977219
https://epubs.siam.org/doi/book/10.1137/1.9781611977219?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Calculus for the Natural Sciences
https://epubs.siam.org/doi/book/10.1137/1.9781611977691?af=R
Calculus for the Natural Sciences. <br/>This textbook is intended for a twosemester course on calculus of one variable. The target audience is comprised of students in biology, chemistry, mathematics, physics, and related disciplines, as well as professionals in these areas. It grew out of the Symbiosis Project at East Tennessee State University.
Calculus for the Natural Sciences. <br/>This textbook is intended for a twosemester course on calculus of one variable. The target audience is comprised of students in biology, chemistry, mathematics, physics, and related disciplines, as well as professionals in these areas. It grew out of the Symbiosis Project at East Tennessee State University.<p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2023/1.9781611977691/1.9781611977691/20230915/1.9781611977691.cover.jpg" alttext="cover image"/></p>
Calculus for the Natural Sciences
doi:10.1137/1.9781611977691
Calculus for the Natural Sciences
20230913T03:50:17Z
10.1137/1.9781611977691
https://epubs.siam.org/doi/book/10.1137/1.9781611977691?af=R
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Fundamentals of Numerical Computation: Julia Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611977011?af=R
Fundamentals of Numerical Computation: Julia Edition. <br/> The invention of MATLAB introduced a new paradigm within research of numerical computation. Those concerned primarily with prototyping and perfecting algorithms, particularly those involving lots of linear algebra, optimization, and differential equations, were happy to adopt MATLAB as a primary computing environment. It offered concise syntax for such problems, freedom from variable types and declarations, compiling, and linking programs, convenient tools for analyzing results, and crossplatform uniformity. There were drawbacks, however, when it came to performance, scalability, and language features beyond the manipulation of vectors and matrices. While MATLAB has steadily made serious progress on closing the performance gap and introducing new language features, there remain computing tasks for which it is not ideally suited.
Fundamentals of Numerical Computation: Julia Edition. <br/> The invention of MATLAB introduced a new paradigm within research of numerical computation. Those concerned primarily with prototyping and perfecting algorithms, particularly those involving lots of linear algebra, optimization, and differential equations, were happy to adopt MATLAB as a primary computing environment. It offered concise syntax for such problems, freedom from variable types and declarations, compiling, and linking programs, convenient tools for analyzing results, and crossplatform uniformity. There were drawbacks, however, when it came to performance, scalability, and language features beyond the manipulation of vectors and matrices. While MATLAB has steadily made serious progress on closing the performance gap and introducing new language features, there remain computing tasks for which it is not ideally suited. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2022/1.9781611977011/1.9781611977011/20230706/1.9781611977011.cover.jpg" alttext="cover image"/></p>
Fundamentals of Numerical Computation: Julia Edition
doi:10.1137/1.9781611977011
Tobin A. Driscoll
Richard J. Braun
Fundamentals of Numerical Computation: Julia Edition
20230706T08:03:06Z
10.1137/1.9781611977011
https://epubs.siam.org/doi/book/10.1137/1.9781611977011?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

The Zen of Exotic Computing
https://epubs.siam.org/doi/book/10.1137/1.9781611977295?af=R
The Zen of Exotic Computing. <br/> “It’s computation, Jim, but not as we know it.”1 The term zen refers to meditation, especially when trying to perceive the true nature of something. The term exotic means “strikingly, excitingly, or mysteriously different or unusual.”2 Both of these terms sum up how I feel when I think about computing. I love computing. I love the idea of, the concept of, computing. I love the process whereby data can be transformed into information in an organized and (usually) predictable fashion. I have spent a wonderful 50+ years architecting digital logicbased systems that do computations, often in unusual ways. While I don’t spend a lot of time developing applications that carry out realworld computations, I have always found it necessary to understand at a fairly deep level what are the properties of such applications, especially ones that represent emerging functionality of interest to me (or a funding agency!). In many cases, this in turn requires understanding how the kernel computations compose together and what is different about them from the underlying kernels in more traditional applications or benchmarks. Thinking about such things has led me to appreciate the potential advantages of looking at computation in “a different way.” 1 Adapted from a lyric in the 1987 song “Star Trekkin”' by the British band The Firm. 2 MerriamWebster online dictionary.
The Zen of Exotic Computing. <br/> “It’s computation, Jim, but not as we know it.”1 The term zen refers to meditation, especially when trying to perceive the true nature of something. The term exotic means “strikingly, excitingly, or mysteriously different or unusual.”2 Both of these terms sum up how I feel when I think about computing. I love computing. I love the idea of, the concept of, computing. I love the process whereby data can be transformed into information in an organized and (usually) predictable fashion. I have spent a wonderful 50+ years architecting digital logicbased systems that do computations, often in unusual ways. While I don’t spend a lot of time developing applications that carry out realworld computations, I have always found it necessary to understand at a fairly deep level what are the properties of such applications, especially ones that represent emerging functionality of interest to me (or a funding agency!). In many cases, this in turn requires understanding how the kernel computations compose together and what is different about them from the underlying kernels in more traditional applications or benchmarks. Thinking about such things has led me to appreciate the potential advantages of looking at computation in “a different way.” 1 Adapted from a lyric in the 1987 song “Star Trekkin”' by the British band The Firm. 2 MerriamWebster online dictionary. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2022/1.9781611977295/1.9781611977295/20230706/1.9781611977295.cover.jpg" alttext="cover image"/></p>
The Zen of Exotic Computing
doi:10.1137/1.9781611977295
Peter M. Kogge
The Zen of Exotic Computing
20230706T04:20:14Z
10.1137/1.9781611977295
https://epubs.siam.org/doi/book/10.1137/1.9781611977295?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Introduction to Applied Mathematics
https://epubs.siam.org/doi/book/10.1137/1.9780961408800?af=R
Introduction to Applied Mathematics. <br/>
Introduction to Applied Mathematics. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/wc/1986/1.9780961408800/1.9780961408800/20230629/1.9780961408800.cover.jpg" alttext="cover image"/></p>
Introduction to Applied Mathematics
doi:10.1137/1.9780961408800
Gilbert Strang
Introduction to Applied Mathematics
20230629T02:48:17Z
10.1137/1.9780961408800
https://epubs.siam.org/doi/book/10.1137/1.9780961408800?af=R
© 1986 by the WellesleyCambridge Press

Solving PDEs in C++
https://epubs.siam.org/doi/book/10.1137/1.9781611972177?af=R
Solving PDEs in C++. <br/>
Solving PDEs in C++. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/cs/2012/1.9781611972177/1.9781611972177/20230629/1.9781611972177.cover.jpg" alttext="cover image"/></p>
Solving PDEs in C++
doi:10.1137/1.9781611972177
Shapira Yair
Solving PDEs in C++
20230629T06:57:41Z
10.1137/1.9781611972177
https://epubs.siam.org/doi/book/10.1137/1.9781611972177?af=R
© 2012 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Foundations of Applied Mathematics, Volume 1: Mathematical Analysis
https://epubs.siam.org/doi/book/10.1137/1.9781611974904?af=R
Foundations of Applied Mathematics, Volume 1: Mathematical Analysis. <br/>
Foundations of Applied Mathematics, Volume 1: Mathematical Analysis. <br/><p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2017/1.9781611974904/1.9781611974904/20230629/1.9781611974904.cover.jpg" alttext="cover image"/></p>
Foundations of Applied Mathematics, Volume 1: Mathematical Analysis
doi:10.1137/1.9781611974904
Jeffrey Humpherys
Tyler J. Jarvis
Emily J. Evans
Foundations of Applied Mathematics, Volume 1: Mathematical Analysis
20230629T08:20:50Z
10.1137/1.9781611974904
https://epubs.siam.org/doi/book/10.1137/1.9781611974904?af=R
© 2017 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Mathematics and Tools for Financial Engineering
https://epubs.siam.org/doi/book/10.1137/1.9781611976762?af=R
Mathematics and Tools for Financial Engineering. <br/> Investment strategies are becoming more sophisticated due to theoretical developments in finance coupled with advanced software tools and fast computational capabilities and due to the increasing number of financial investment options that are available. The traditional way of solving financial problems and making investment decisions has been replaced with intelligent techniques that involve good understanding of the theory for modeling the dynamic behavior of assets and investments, optimization techniques to choose the best solution from a set of many feasible solutions, and software tools to simulate the theory and generate solutions, evaluate performance and risks, and make predictions.
Mathematics and Tools for Financial Engineering. <br/> Investment strategies are becoming more sophisticated due to theoretical developments in finance coupled with advanced software tools and fast computational capabilities and due to the increasing number of financial investment options that are available. The traditional way of solving financial problems and making investment decisions has been replaced with intelligent techniques that involve good understanding of the theory for modeling the dynamic behavior of assets and investments, optimization techniques to choose the best solution from a set of many feasible solutions, and software tools to simulate the theory and generate solutions, evaluate performance and risks, and make predictions. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2021/1.9781611976762/1.9781611976762/20230629/1.9781611976762.cover.jpg" alttext="cover image"/></p>
Mathematics and Tools for Financial Engineering
doi:10.1137/1.9781611976762
Petros A. Ioannou
Mathematics and Tools for Financial Engineering
20230629T08:28:00Z
10.1137/1.9781611976762
https://epubs.siam.org/doi/book/10.1137/1.9781611976762?af=R
© 2021 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

The Less Is More Linear Algebra of Vector Spaces and Matrices
https://epubs.siam.org/doi/book/10.1137/1.9781611977400?af=R
The Less Is More Linear Algebra of Vector Spaces and Matrices. <br/> Linear algebra is one of the pillars of mathematics and a prototype of it in several ways. It trains the mind to organize ideas and results so as to make the most efficient use of them. Linear algebra is deeply theoretical at its core, yet it plays a crucial role in many extremely practical applications. The power of linear algebra is that it is developed for objects satisfying certain conditions that have nothing to do with computing and numbers, and at the same time it is crucial when it comes to simplifying and streamlining numerical calculations.
The Less Is More Linear Algebra of Vector Spaces and Matrices. <br/> Linear algebra is one of the pillars of mathematics and a prototype of it in several ways. It trains the mind to organize ideas and results so as to make the most efficient use of them. Linear algebra is deeply theoretical at its core, yet it plays a crucial role in many extremely practical applications. The power of linear algebra is that it is developed for objects satisfying certain conditions that have nothing to do with computing and numbers, and at the same time it is crucial when it comes to simplifying and streamlining numerical calculations. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2022/1.9781611977400/1.9781611977400/20230629/1.9781611977400.cover.jpg" alttext="cover image"/></p>
The Less Is More Linear Algebra of Vector Spaces and Matrices
doi:10.1137/1.9781611977400
Daniela Calvetti
Erkki Somersalo
The Less Is More Linear Algebra of Vector Spaces and Matrices
20230629T08:32:00Z
10.1137/1.9781611977400
https://epubs.siam.org/doi/book/10.1137/1.9781611977400?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611977622?af=R
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition. <br/> Preface to the Second Edition: The second edition features two significant enhancements to the first edition. 1. Python codes were added on top of the existing MATLAB codes to illustrate and demonstrate different aspects of the algorithmic and applicative nature of nonlinear optimization. Since the first edition's publication, Python has become one of the leading software languages for scientific computing and is used in many applications, most notably those arising in data science. Readers interested in implementation may choose to follow either the MATLAB or Python codes which appear, sometimes literally, side by side. A new section on the Python module CVXPY (Section 8.5) describes how to solve convex optimization problems using Python.
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition. <br/> Preface to the Second Edition: The second edition features two significant enhancements to the first edition. 1. Python codes were added on top of the existing MATLAB codes to illustrate and demonstrate different aspects of the algorithmic and applicative nature of nonlinear optimization. Since the first edition's publication, Python has become one of the leading software languages for scientific computing and is used in many applications, most notably those arising in data science. Readers interested in implementation may choose to follow either the MATLAB or Python codes which appear, sometimes literally, side by side. A new section on the Python module CVXPY (Section 8.5) describes how to solve convex optimization problems using Python. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/mo/2023/1.9781611977622/1.9781611977622/20230629/1.9781611977622.cover.jpg" alttext="cover image"/></p>
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
doi:10.1137/1.9781611977622
Amir Beck
Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
20230629T08:36:40Z
10.1137/1.9781611977622
https://epubs.siam.org/doi/book/10.1137/1.9781611977622?af=R
© 2023 by the Society for Industrial and Applied Mathematics

A First Course in Options Pricing Theory
https://epubs.siam.org/doi/book/10.1137/1.9781611977646?af=R
A First Course in Options Pricing Theory. <br/> Financial derivatives, such as stock options for instance, are indispensable instruments in modern financial markets. The introduction of options markets in the early 1970s, and the continuous appearance of new types of complex derivative contracts, resulted in a rapid growth of interest in the theoretical aspects of options valuation. Since its inception in 1900 by the French mathematician Bachelier, options pricing theory has evolved into a modern discipline with a vast literature and dedicated university courses. While still considered in large part an advanced topic, it has become more and more common to find courses on options pricing theory in the undergraduate program of major universities all around the world. Moreover, financial institutions have since long recognized the pivotal role of mathematical models for their proper functionality and consistently offer employment opportunities for mathematicians.
A First Course in Options Pricing Theory. <br/> Financial derivatives, such as stock options for instance, are indispensable instruments in modern financial markets. The introduction of options markets in the early 1970s, and the continuous appearance of new types of complex derivative contracts, resulted in a rapid growth of interest in the theoretical aspects of options valuation. Since its inception in 1900 by the French mathematician Bachelier, options pricing theory has evolved into a modern discipline with a vast literature and dedicated university courses. While still considered in large part an advanced topic, it has become more and more common to find courses on options pricing theory in the undergraduate program of major universities all around the world. Moreover, financial institutions have since long recognized the pivotal role of mathematical models for their proper functionality and consistently offer employment opportunities for mathematicians. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2023/1.9781611977646/1.9781611977646/20230629/1.9781611977646.cover.jpg" alttext="cover image"/></p>
A First Course in Options Pricing Theory
doi:10.1137/1.9781611977646
Simone Calogero
A First Course in Options Pricing Theory
20230629T08:35:20Z
10.1137/1.9781611977646
https://epubs.siam.org/doi/book/10.1137/1.9781611977646?af=R
© 2023 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Introduction to Numerical Linear Algebra
https://epubs.siam.org/doi/book/10.1137/1.9781611976922?af=R
Introduction to Numerical Linear Algebra. <br/> G. H. Hardy published A Mathematician's Apology in 1940. The sense of the term is that of apologia, a defense of a field. It could be said (and some of my friends have said) that a more accurate title for the present piece would have been Confessions of a Numerical Analyst. To be sure, this essay differs in many ways from Hardy's, containing more biographical material and also more mathematics, especially in the second half. But its purpose is the same, a serious and personal meditation about mathematics
Introduction to Numerical Linear Algebra. <br/> G. H. Hardy published A Mathematician's Apology in 1940. The sense of the term is that of apologia, a defense of a field. It could be said (and some of my friends have said) that a more accurate title for the present piece would have been Confessions of a Numerical Analyst. To be sure, this essay differs in many ways from Hardy's, containing more biographical material and also more mathematics, especially in the second half. But its purpose is the same, a serious and personal meditation about mathematics <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2022/1.9781611976922/1.9781611976922/20230111/1.9781611976922.cover.jpg" alttext="cover image"/></p>
Introduction to Numerical Linear Algebra
doi:10.1137/1.9781611976922
Christoph Börgers
Introduction to Numerical Linear Algebra
20230111T02:32:52Z
10.1137/1.9781611976922
https://epubs.siam.org/doi/book/10.1137/1.9781611976922?af=R
© 2022 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Handbook of Writing for the Mathematical Sciences, Third Edition
https://epubs.siam.org/doi/book/10.1137/1.9781611976106?af=R
Handbook of Writing for the Mathematical Sciences, Third Edition. <br/> In this book I aim to describe most of what a scientist needs to know about mathematical writing. Although the focus in on mathematical writing, most of the book is applicable to scientific writing in general.
Handbook of Writing for the Mathematical Sciences, Third Edition. <br/> In this book I aim to describe most of what a scientist needs to know about mathematical writing. Although the focus in on mathematical writing, most of the book is applicable to scientific writing in general. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/ot/2020/1.9781611976106/1.9781611976106/20201019/1.9781611976106.cover.jpg" alttext="cover image"/></p>
Handbook of Writing for the Mathematical Sciences, Third Edition
doi:10.1137/1.9781611976106
Nicholas J. Higham
Handbook of Writing for the Mathematical Sciences, Third Edition
20201019T07:31:22Z
10.1137/1.9781611976106
https://epubs.siam.org/doi/book/10.1137/1.9781611976106?af=R
© 2020 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.

Riemann Problems and Jupyter Solutions
https://epubs.siam.org/doi/book/10.1137/1.9781611976212?af=R
Riemann Problems and Jupyter Solutions. <br/> Aims and scope This book addresses an important class of mathematical problems—the Riemann problem—for firstorder hyperbolic partial differential equations (PDEs). Such PDEs arise when modeling wave propagation in applications such as fluid dynamics, traffic flow, elasticity, and electromagnetics. The solution of the Riemann problem captures essential information about such models and is the key ingredient in modern numerical methods for their solution.
Riemann Problems and Jupyter Solutions. <br/> Aims and scope This book addresses an important class of mathematical problems—the Riemann problem—for firstorder hyperbolic partial differential equations (PDEs). Such PDEs arise when modeling wave propagation in applications such as fluid dynamics, traffic flow, elasticity, and electromagnetics. The solution of the Riemann problem captures essential information about such models and is the key ingredient in modern numerical methods for their solution. <p><img src="https://epubs.siam.org/na101/home/literatum/publisher/siam/books/content/fa/2020/1.9781611976212/1.9781611976212/20200626/1.9781611976212.cover.jpg" alttext="cover image"/></p>
Riemann Problems and Jupyter Solutions
doi:10.1137/1.9781611976212
David I. Ketcheson
Randall J. LeVeque
Mauricio J. del Razo
Riemann Problems and Jupyter Solutions
20200626T01:37:47Z
10.1137/1.9781611976212
https://epubs.siam.org/doi/book/10.1137/1.9781611976212?af=R
© 2020 by the Society for Industrial and Applied MathematicsAll rights reserved. Printed in the United States of America. No part of this book may be reproduced, stored, or transmitted in any manner without the written permission of the publisher. For information, write to the Society for Industrial and Applied Mathematics, 3600 Market Street, 6th Floor, Philadelphia, PA 191042688 USA.