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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
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Àsgeir Birkisson
Automatic Reformulation of ODEs to Systems of First-Order Equations
Article in
ACM Trans. Math. Softw., ACM,
2018 |
Tools:
Chebfun
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M. Luers, M. Sagebaum, S. Mann, J. Backhaus, D. Großmann, 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
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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
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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
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Vakhtang Putkaradze, Stuart Rogers
Constraint Control of Nonholonomic Mechanical Systems
Article in
Journal of Nonlinear Science, 2018 |
Application Area:
Mechanical Engineering
Tools:
ADiGator
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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
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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
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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
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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
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Bruce Christianson, Shaun A. Forth, Andreas Griewank
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation
Taylor & Francis,
2018 |
Theory & Techniques:
General
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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
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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
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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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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
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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
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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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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
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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
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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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