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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
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
Harshitha Menon, Michael O. Lam, Daniel Osei-Kuffuor, Markus Schordan, Scott Lloyd, Kathryn Mohror, Jeffrey Hittinger
ADAPT: algorithmic differentiation applied to floating-point precision tuning
Conference proceeding, Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018, Dallas, TX, USA, November 11--16, 2018, IEEE / ACM, 2018
Application Area:
Error Analysis
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
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
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
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
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
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
van Merriënboer, Bart, Olivier Breuleux, Arnaud Bergeron, Pascal Lamblin
Automatic differentiation in ML: Where we are and where we should be going
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Theory & Techniques:
General, Implementation Strategies
Àsgeir Birkisson
Automatic Reformulation of ODEs to Systems of First-Order Equations
Article in ACM Trans. Math. Softw., ACM, 2018
Tools:
Chebfun
Navjot Kukreja, Jan Hückelheim, Gerard J. Gorman
Backpropagation for long sequences: beyond memory constraints with constant overheads
Article in CoRR, 2018
Theory & Techniques:
Checkpointing
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
Theory & Techniques:
Generalized Jacobian, Reverse Mode
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
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
Theory & Techniques:
Generalized Jacobian
Soeren Laue, Matthias Mitterreiter, Joachim Giesen
Computing Higher Order Derivatives of Matrix and Tensor Expressions
Conference proceeding, Advances in Neural Information Processing Systems, Curran Associates, Inc., 2018
Theory & Techniques:
Hierarchical Approach
Vakhtang Putkaradze, Stuart Rogers
Constraint Control of Nonholonomic Mechanical Systems
Article in Journal of Nonlinear Science, 2018
Application Area:
Mechanical Engineering
Tools:
ADiGator
Bruce Christianson
Differentiating through conjugate gradient
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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