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Name: Springer Math
Type: Organization
Bio: Source code for books published by Springer Math
Name: Springer Math
Type: Organization
Bio: Source code for books published by Springer Math
Sage source code for the computation of graphs and proofs from "Adventures in Graph Theory" by David Joyner and Caroline Grant Melles
Source code for 'Dynamical Systems with Applications using MATLAB®, 2ed' by Stephen Lynch http://www.springer.com/book/9783319068190
Source code for 'Dynamical Systems with Applications Using Python' by Stephen Lynch
This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.
Source code accompanying 'Mathematics of Epidemics on Networks' by Kiss, Miller, and Simon http://www.springer.com/us/book/9783319508047 . Documentation for the software package is at https://epidemicsonnetworks.readthedocs.io/en/latest/
Source code for 'Methods of Applied Mathematics with a Software Overview' by Jon H. Davis http://www.springer.com/book/9783319433691
Source code for Multiple Criteria Decision Aid by Jason Papathanasiou, Nikolaos Ploskas
Matlab codes accompanying Numerical Methods for Stochastic Partial Differential Equations with White Noise
MATLAB codes accompanying "Numerical Linear Algebra Theory" by Larisa Beilina, Evgenii Karchevskii, and Mikhail Karchevskii
MATLAB code from K. Deergha's book on signal processing
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.