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Automatic Differentiation of Algorithms

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Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Differentiation Methods for Industrial Strength Problems
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    Chapter 2 Automatic Differentiation Tools in Optimization Software
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    Chapter 3 Using Automatic Differentiation for Second-Order Matrix-free Methods in PDE-constrained Optimization
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    Chapter 4 Performance Issues in Automatic Differentiation on Superscalar Processors
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    Chapter 5 Present and Future Scientific Computation Environments
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    Chapter 6 A Case Study of Computational Differentiation Applied to Neutron Scattering
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    Chapter 7 Odyssée versus Hand Differentiation of a Terrain Modeling Application
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    Chapter 8 Automatic Differentiation for Modern Nonlinear Regression
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    Chapter 9 Sensitivity Analysis and Parameter Tuning of a Sea-Ice Model
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    Chapter 10 Electron Paramagnetic Resonance, Optimization and Automatic Differentiation
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    Chapter 11 Continuous Optimal Control Sensitivity Analysis with AD
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    Chapter 12 Application of Automatic Differentiation to Race Car Performance Optimisation
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    Chapter 13 Globalization of Pantoja’s Optimal Control Algorithm
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    Chapter 14 Analytical Aspects and Practical Pitfalls in Technical Applications of AD
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    Chapter 15 Nonlinear Observer Design Using Automatic Differentiation
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    Chapter 16 On the Iterative Solution of Adjoint Equations
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    Chapter 17 Aerofoil Optimisation via AD of a Multigrid Cell-Vertex Euler Flow Solver
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    Chapter 18 Automatic Differentiation and the Adjoint State Method
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    Chapter 19 Efficient Operator Overloading AD for Solving Nonlinear PDEs
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    Chapter 20 Integrating AD with Object-Oriented Toolkits for High-Performance Scientific Computing
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    Chapter 21 Optimal Sizing of Industrial Structural Mechanics Problems Using AD
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    Chapter 22 Second Order Exact Derivatives to Perform Optimization on Self-Consistent Integral Equations Problems
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    Chapter 23 Accurate Gear Tooth Contact and Sensitivity Computation for Hypoid Bevel Gears
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    Chapter 24 Optimal Laser Control of Chemical Reactions Using AD
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    Chapter 25 Automatically Differentiating MPI-1 Datatypes: The Complete Story
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    Chapter 26 Sensitivity Analysis Using Parallel ODE Solvers and Automatic Differentiation in C: SensPVODE and ADIC
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    Chapter 27 A Parallel Hierarchical Approach for Automatic Differentiation
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    Chapter 28 New Results on Program Reversals
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    Chapter 29 Elimination Techniques for Cheap Jacobians
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    Chapter 30 AD Tools and Prospects for Optimal AD in CFD Flux Jacobian Calculations
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    Chapter 31 Reducing the Number of AD Passes for Computing a Sparse Jacobian Matrix
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    Chapter 32 Verifying Jacobian Sparsity
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    Chapter 33 Recomputations in Reverse Mode AD
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    Chapter 34 Minimizing the Tape Size
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    Chapter 35 Adjoining Independent Computations
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    Chapter 36 Complexity Analysis of Automatic Differentiation in the Hyperion Software
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    Chapter 37 Expression Templates and Forward Mode Automatic Differentiation
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    Chapter 38 Application of AD to a Family of Periodic Functions
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    Chapter 39 FAD Method to Compute Second Order Derivatives
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    Chapter 40 Application of Higher Order Derivatives to Parameterization
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    Chapter 41 Efficient High-Order Methods for ODEs and DAEs
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    Chapter 42 From Rounding Error Estimation to Automatic Correction with Automatic Differentiation
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    Chapter 43 New Applications of Taylor Model Methods
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    Chapter 44 Taylor Models in Deterministic Global Optimization
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    Chapter 45 Towards a Universal Data Type for Scientific Computing
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Title
Automatic Differentiation of Algorithms
Published by
Springer New York, November 2013
DOI 10.1007/978-1-4613-0075-5
ISBNs
978-1-4612-6543-6, 978-1-4613-0075-5
Editors

Corliss, George, Faure, Christèle, Griewank, Andreas, Hascoët, Laurent, Naumann, Uwe

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 25%
Researcher 2 13%
Student > Doctoral Student 2 13%
Lecturer > Senior Lecturer 1 6%
Professor > Associate Professor 1 6%
Other 1 6%
Unknown 5 31%
Readers by discipline Count As %
Engineering 5 31%
Mathematics 1 6%
Chemical Engineering 1 6%
Physics and Astronomy 1 6%
Economics, Econometrics and Finance 1 6%
Other 0 0%
Unknown 7 44%