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Order by: [Title], [Author], [Editor], [Year]
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
not yet classified
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
Alexander Hück, Christian Bischof, Max Sagebaum, Nicolas R. Gauger, Benjamin Jurgelucks, Eric Larour, Gilberto Perez
A usability case study of algorithmic differentiation tools on the ISSM ice sheet model
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
Isabelle Charpentier, Jens Gustedt
Arbogast: Higher order automatic differentiation for special functions with Modular C
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
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
not yet classified
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
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
not yet classified
Bruce Christianson
Differentiating through conjugate gradient
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
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
not yet classified
Kshitij Kulshreshtha, Sri Hari Krishna Narayanan, Julie Bessac, Kaitlyn MacIntyre
Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Koichi Kubota
Enumeration of subdifferentials of piecewise linear functions with abs-normal form
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
H. Martin Bücker, Johannes Willkomm
Estimating the expansion coefficients of a geomagnetic field model using first-order derivatives of associated Legendre functions
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Application Area:
Geophysics
Tools:
ADiMat
Theory & Techniques:
Hierarchical Approach
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
John D. Pryce, Nedialko S. Nedialkov, Guangning Tan, Xiao Li
How AD can help solve differential-algebraic equations
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Andreas Griewank, Richard Hasenfelder, Manuel Radons, Lutz Lehmann, Tom Streubel
Integrating Lipschitzian dynamical systems using piecewise algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Siegfried M. Rump
Mathematically rigorous global optimization in floating-point arithmetic
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Valérie Pascual, Laurent Hascoët
Mixed-language automatic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Bradley M. Bell, Kasper Kristensen
Newton step methods for AD of an objective defined using implicit functions
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
C. G. Petra, F. Qiang, M. Lubin, J. Huchette
On efficient Hessian computation using the edge pushing algorithm in Julia
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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