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Order by: [Title], [Author], [Editor], [Year]
Jeffrey Mark Siskind, Barak A. Pearlmutter
Divide-and-conquer checkpointing for arbitrary programs with no user annotation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Theory & Techniques:
Checkpointing
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
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
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
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
Kshitij Kulshreshtha, Sri Hari Krishna Narayanan, Julie Bessac, Kaitlyn MacIntyre
Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Koichi Kubota
Enumeration of subdifferentials of piecewise linear functions with abs-normal form
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
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
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
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
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
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
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
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
Bruce Christianson
Differentiating through conjugate gradient
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
Isabelle Charpentier, Bruno Cochelin
Towards a full higher order AD-based continuation and bifurcation framework
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
H. Martin Bücker, Johannes Willkomm
Estimating the expansion coefficients of a geomagnetic field model using first-order derivatives of associated Legendre functions
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
Application Area:
Geophysics
Tools:
ADiMat
Theory & Techniques:
Hierarchical Approach
Bradley M. Bell, Kasper Kristensen
Newton step methods for AD of an objective defined using implicit functions
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified
Benjamin Jurgelucks, Leander Claes, Andrea Walther, Bernd Henning
Optimization of triple-ring electrodes on piezoceramic transducers using algorithmic differentiation
Article in Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis, 2018
not yet classified

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