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Order by: [Title], [Author], [Editor], [Year]
Daniele Casanova, Robin S. Sharp, Mark Final, Bruce Christianson, Pat Symonds
Application of Automatic Differentiation to Race Car Performance Optimisation
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
David E. Keyes, Paul D. Hovland, Lois C. McInnes, Widodo Samyono
Using Automatic Differentiation for Second-order Matrix-free Methods in PDE-Constrained Optimization
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
not yet classified
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
Laurent Hascoët, Stefka Fidanova, Christophe Held
Adjoining Independent Computations
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Application Area:
Computational Fluid Dynamics
Tools:
TAPENADE
Theory & Techniques:
Reverse Mode
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
Mohamed Tadjouddine, Shaun A. Forth, John D. Pryce
AD Tools and Prospects for Optimal AD in CFD Flux Jacobian Calculations
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Application Area:
Computational Fluid Dynamics
Tools:
AD01, ADIFOR, TAMC
Shahadat Hossain, Trond Steihaug
Reducing the Number of AD Passes for Computing a Sparse Jacobian Matrix
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer, 2002
Theory & Techniques:
Sparsity
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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