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Order by: [Title], [Author], [Editor], [Year]
Andrea Walther, Andreas Griewank
New Results on Program Reversals
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Checkpointing
Andreas Griewank, Christo Mitev
Verifying Jacobian Sparsity
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Sparsity
Edgar J. Soulié, Christèle Faure, Théo Berclaz, Michel Geoffroy
Electron Paramagnetic Resonance, Optimization and Automatic Differentiation
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
Jason Abate, Steve Benson, Lisa Grignon, Paul D. Hovland, Lois C. McInnes, Boyana Norris
Integrating AD with Object-Oriented Toolkits for High-performance Scientific Computing
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Toolkits
Jean-Daniel Beley, Stephane Garreau, Frederic Thevenon, Mohamed Masmoudi
Application of Higher Order Derivatives to Parameterization
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
Jong G. Kim, Paul D. Hovland
Sensitivity Analysis and Parameter Tuning of a Sea-Ice Model
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
José Grimm
Complexity Analysis of Automatic Differentiation in the Hyperion Software
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
Mark S. Gockenbach, Daniel R. Reynolds, William W. Symes
Automatic Differentiation and the Adjoint State Method
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Adjoint
Michael B. Giles
On the Iterative Solution of Adjoint Equations
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Adjoint, Fixpoint, Reverse Mode
R. Giering, T. Kaminski
Using TAMC to generate efficient adjoint code: Comparison of automatically generated code for evaluation of first and second order derivatives to hand written code from the Minpack-2 collection
Automatic Differentiation for Adjoint Code Generation, INRIA, 1998
Application Area:
General
Tools:
TAMC
Theory & Techniques:
Hessian, Performance
Ralf Giering, Thomas Kaminski
Recomputations in Reverse Mode AD
Automatic Differentiation: From Simulation to Optimization, Springer, 2002
Application Area:
General
Tools:
TAF, TAMC
Theory & Techniques:
Recomputation
Wolfram Klein, Andreas Griewank, Andrea Walther
Differentiation Methods for Industrial Strength Problems
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Application Area:
Electrical Engineering
Tools:
ADIFOR, ADOL-C, Odyssee
Yuri G. Evtushenko, E. S. Zasuhina, V. I. Zubov
FAD Method to Compute Second Order Derivatives
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Hessian

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