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Automatic Differentiation: Applications, Theory, and Implementations

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Cover of 'Automatic Differentiation: Applications, Theory, and Implementations'

Table of Contents

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    Book Overview
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    Chapter 1 Perspectives on Automatic Differentiation: Past, Present, and Future?
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    Chapter 2 Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities
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    Chapter 3 Solutions of ODEs with Removable Singularities
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    Chapter 4 Automatic Propagation of Uncertainties
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    Chapter 5 High-Order Representation of Poincarée Maps
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    Chapter 6 Computation of Matrix Permanent with Automatic Differentiation
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    Chapter 7 Computing Sparse Jacobian Matrices Optimally
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    Chapter 8 Application of AD-based Quasi-Newton Methods to Stiff ODEs
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    Chapter 9 Reduction of Storage Requirement by Checkpointing for Time-Dependent Optimal Control Problems in ODEs
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    Chapter 10 Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation
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    Chapter 11 Flattening Basic Blocks
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    Chapter 12 The Adjoint Data-Flow Analyses: Formalization, Properties, and Applications
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    Chapter 13 Semiautomatic Differentiation for Efficient Gradient Computations
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    Chapter 14 Computing Adjoints with the NAGWare Fortran 95 Compiler
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    Chapter 15 Extension of TAPENADE toward Fortran 95
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    Chapter 16 A Macro Language for Derivative Definition in ADiMat
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    Chapter 17 Transforming Equation-Based Models in Process Engineering
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    Chapter 18 Simulation and Optimization of the Tevatron Accelerator
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    Chapter 19 Periodic Orbits of Hybrid Systems and Parameter Estimation via AD
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    Chapter 20 Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization
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    Chapter 21 Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization
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    Chapter 22 Automatic Differentiation: A Tool for Variational Data Assimilation and Adjoint Sensitivity Analysis for Flood Modeling
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    Chapter 23 Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF
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    Chapter 24 Tangent Linear and Adjoint Versions of NASA/GMAO’s Fortran 90 Global Weather Forecast Model
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    Chapter 25 Efficient Sensitivities for the Spin-Up Phase
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    Chapter 26 Streamlined Circuit Device Model Development with fREEDAR® ãnd ADOL-C
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    Chapter 27 Adjoint Differentiation of a Structural Dynamics Solver
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    Chapter 28 A Bibliography of Automatic Differentiation
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Title
Automatic Differentiation: Applications, Theory, and Implementations
Published by
Springer Science & Business Media, February 2006
DOI 10.1007/3-540-28438-9
ISBNs
978-3-54-028438-3, 978-3-54-028403-1
Editors

Bücker, Martin, Corliss, George, Naumann, Uwe, Hovland, Paul, Norris, Boyana

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 7%
United Kingdom 1 4%
United States 1 4%
Romania 1 4%
Unknown 23 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 21%
Student > Master 5 18%
Student > Ph. D. Student 4 14%
Professor > Associate Professor 3 11%
Student > Bachelor 2 7%
Other 8 29%
Readers by discipline Count As %
Computer Science 8 29%
Engineering 4 14%
Mathematics 3 11%
Earth and Planetary Sciences 3 11%
Unspecified 2 7%
Other 8 29%