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Order by: [Title], [Author], [Editor], [Year]
Benjamin Jurgelucks, Leander Claes, Andrea Walther, Bernd Henning
Optimization of triple-ring electrodes on piezoceramic transducers using algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Bruce Christianson, Shaun A. Forth, Andreas Griewank
Preface
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
General
Filip Srajer, Zuzana Kukelova, Andrew Fitzgibbon
A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Tools:
Adept, ADiMat, ADOL-C, DiffSharp, TAPENADE, Theano
Jeffrey Mark Siskind, Barak A. Pearlmutter
Divide-and-conquer checkpointing for arbitrary programs with no user annotation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
Checkpointing
Kamil A. Khan
Branch-locking AD techniques for nonsmooth composite functions and nonsmooth implicit functions
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
Generalized Jacobian, Reverse Mode
Lisa Kusch, Tim Albring, Andrea Walther, Nicolas R. Gauger
A one-shot optimization framework with additional equality constraints applied to multi-objective aerodynamic shape optimization
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Max Sagebaum, Tim Albring, Nicolas R. Gauger
Expression templates for primal value taping in the reverse mode of algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Application Area:
General
Tools:
CoDiPack
Theory & Techniques:
Adjoint, Black Box, Code Optimization, Implementation Strategies, Performance, Reverse Mode
Mu Wang, Guang Lin, Alex Pothen
Using automatic differentiation for compressive sensing in uncertainty quantification
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Olivier Mullier, Alexandre Chapoutot, dit Sandretto, Julien Alexandre
Validated computation of the local truncation error of Runge--Kutta methods with automatic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Paul I. Barton, Kamil A. Khan, Peter Stechlinski, Harry A. J. Watson
Computationally relevant generalized derivatives: theory, evaluation and applications
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
Generalized Jacobian
Richard D. Neidinger, Benjamin Altman
Comparing high-order multivariate AD methods
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Sabrina Fiege, Andrea Walther, Kshitij Kulshreshtha, Andreas Griewank
Algorithmic differentiation for piecewise smooth functions: a case study for robust optimization
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Ulrich Römer, Mahesh Narayanamurthi, Adrian Sandu
Solving parameter estimation problems with discrete adjoint exponential integrators
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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