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Order by: [Title], [Author], [Editor], [Year]
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
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
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
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
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
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
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
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
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
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
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
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
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

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