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Order by: [Title], [Author], [Editor], [Year]
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
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
Theory & Techniques:
Piecewise Linear
Andreas Griewank, Tom Streubel, Lutz Lehmann, Manuel Radons, Richard Hasenfelder
Piecewise linear secant approximation via algorithmic piecewise differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
Piecewise Linear
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
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
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
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
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
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
Yingyi Li, Haibin Zhang, Zhibao Li, Huan Gao
Proximal gradient method with automatic selection of the parameter by automatic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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