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Order by: [Title], [Author], [Editor], [Year]
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
Markus Towara, Uwe Naumann
SIMPLE adjoint message passing
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
Shahadat Hossain, Nasrin Hakim Mithila
Pattern graph for sparse Hessian matrix determination
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
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
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
Viktor Mosenkis, Uwe Naumann
On lower bounds for optimal Jacobian accumulation
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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