Publications from 2018
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Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, Moritz Diehl
CasADi -- A software framework for nonlinear optimization and optimal control
Article in Mathematical Programming Computation, 2018
Tools:
CasADi
Àsgeir Birkisson
Automatic Reformulation of ODEs to Systems of First-Order Equations
Article in ACM Trans. Math. Softw., ACM, 2018
Tools:
Chebfun
M. Luers, M. Sagebaum, S. Mann, J. Backhaus, D. Gro▀mann, N. R. Gauger
Adjoint-based Volumetric Shape Optimization of Turbine Blades
Article in AIAA 2018-3638, 2018
Application Area:
Aerodynamics, Computational Fluid Dynamics, Optimization, Shape optimization
Tools:
CoDiPack
Theory & Techniques:
Adjoint, Black Box, Fixpoint, Performance, Reverse Mode
Belmiro P. M. Duarte, Guillaume Sagnol, Weng Kee Wong
An algorithm based on semidefinite programming for finding minimax optimal designs
Article in Computational Statistics & Data Analysis, 2018
Application Area:
Optimization
Tools:
ADiMat
B. P. M. Duarte, W. K. Wong, H. Dette
Adaptive grid semidefinite programming for finding optimal designs
Article in Statistics and Computing, 2018
Application Area:
Optimization
Tools:
ADiMat
Vakhtang Putkaradze, Stuart Rogers
Constraint Control of Nonholonomic Mechanical Systems
Article in Journal of Nonlinear Science, 2018
Application Area:
Mechanical Engineering
Tools:
ADiGator
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
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
Alexander Hück, Sebastian Kreutzer, Danny Messig, Arne Scholtissek, Christian Bischof, Christian Hasse
Application of Algorithmic Differentiation for Exact Jacobians to the Universal Laminar Flame Solver
Conference proceeding, Computational Science -- ICCS 2018, Springer International Publishing, 2018
Application Area:
Computational Fluid Dynamics
Tools:
CoDiPack
Jan C. Hückelheim, Paul D. Hovland, Michelle M. Strout, Jens-Dominik Müller
Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Application Area:
Computational Fluid Dynamics
Tools:
TAPENADE
Theory & Techniques:
Adjoint, Code Optimization, control-flow reversal, Data Flow Analysis, data-flow reversal, Implementation Strategies, Parallelism, Performance, Reverse Mode, Source transformation
Bruce Christianson, Shaun A. Forth, Andreas Griewank
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation
2018
Theory & Techniques:
General
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
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
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
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
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
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
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
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
Laurent Hascoët, Mathieu Morlighem
Source-to-source adjoint Algorithmic Differentiation of an ice sheet model written in C
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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