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Order by: [Title], [Author], [Editor], [Year]
Bruce Christianson
A Leibniz Notation for Automatic Differentiation
Recent Advances in Algorithmic Differentiation, Springer, 2012
Theory & Techniques:
General
Hany S. Abdel-Khalik, Paul D. Hovland, Andrew Lyons, Tracy E. Stover, Jean Utke
A Low Rank Approach to Automatic Differentiation
Advances in Automatic Differentiation, Springer, 2008
Tools:
OpenAD
Theory & Techniques:
Jacobian-vector product
Salvatore Cuomo, Luisa D'Amore, Mariarosaria Rizzardi, Almerico Murli
A Modification of Weeks' Method for Numerical Inversion of the Laplace Transform in the Real Case Based on Automatic Differentiation
Advances in Automatic Differentiation, Springer, 2008
Tools:
FADBAD/TADIFF
Sanjukta Bhowmick, Paul D. Hovland
A Polynomial-Time Algorithm for Detecting Directed Axial Symmetry in Hessian Computational Graphs
Advances in Automatic Differentiation, Springer, 2008
Theory & Techniques:
Computational Graph, Hessian
Alexey Radul, Barak A. Pearlmutter, Jeffrey Mark Siskind
AD in Fortran: Implementation via Prepreprocessor
Recent Advances in Algorithmic Differentiation, Springer, 2012
Tools:
Farfallen
Theory & Techniques:
Implementation Strategies
Markus Beckers, Viktor Mosenkis, Uwe Naumann
Adjoint Mode Computation of Subgradients for McCormick Relaxations
Recent Advances in Algorithmic Differentiation, Springer, 2012
not yet classified
Jan Riehme, Andrea Walther, Jörg Stiller, Uwe Naumann
Adjoints for Time-Dependent Optimal Control
Advances in Automatic Differentiation, Springer, 2008
Application Area:
Optimal Control
Tools:
NAGWare Fortran 95
Christian H. Bischof, H. Martin Bücker, Paul D. Hovland, Uwe Naumann, Jean Utke
Advances in Automatic Differentiation
Springer, 2008
Theory & Techniques:
General
Bradley M. Bell, James V. Burke
Algorithmic Differentiation of Implicit Functions and Optimal Values
Advances in Automatic Differentiation, Springer, 2008
Tools:
ADOL-C, CppAD
Theory & Techniques:
Fixpoint
Abhishek Kr. Gupta, Shaun A. Forth
An AD-Enabled Optimization ToolBox in LabVIEW™
Recent Advances in Algorithmic Differentiation, Springer, 2012
not yet classified
Jieqiu Chen, Paul Hovland, Todd Munson, Jean Utke
An Integer Programming Approach to Optimal Derivative Accumulation
Recent Advances in Algorithmic Differentiation, Springer, 2012
Theory & Techniques:
Computational Graph
Emre Özkaya, Anil Nemili, Nicolas R. Gauger
Application of Automatic Differentiation to an Incompressible URANS Solver
Recent Advances in Algorithmic Differentiation, Springer, 2012
Theory & Techniques:
Adjoint, Parallelism
Azamat Mametjanov, Boyana Norris, Xiaoyan Zeng, Beth Drewniak, Jean Utke, Mihai Anitescu, Paul Hovland
Applying Automatic Differentiation to the Community Land Model
Recent Advances in Algorithmic Differentiation, Springer, 2012
Tools:
OpenAD
Markus Grabner, Thomas Pock, Tobias Gross, Bernhard Kainz
Automatic Differentiation for GPU-Accelerated 2D/3D Registration
Advances in Automatic Differentiation, Springer, 2008
Application Area:
Biomedicine
Jeffrey A. Fike, Juan J. Alonso
Automatic Differentiation Through the Use of Hyper-Dual Numbers for Second Derivatives
Recent Advances in Algorithmic Differentiation, Springer, 2012
Theory & Techniques:
Hessian
Atya Elsheikh, Wolfgang Wiechert
Automatic Sensitivity Analysis of DAE-systems Generated from Equation-Based Modeling Languages
Advances in Automatic Differentiation, Springer, 2008
Application Area:
Differential-Algebraic Equation
Uwe Naumann
Call Tree Reversal is NP-Complete
Advances in Automatic Differentiation, Springer, 2008
Theory & Techniques:
Adjoint, Checkpointing
Joel Andersson, Johan \AAkesson, Moritz Diehl
CasADI: A Symbolic Package for Automatic Differentiation and Optimal Control
Recent Advances in Algorithmic Differentiation, Springer, 2012
Tools:
CasADI
H. Martin Bücker, Monika Petera, Andre Vehreschild
Code Optimization Techniques in Source Transformations for Interpreted Languages
Advances in Automatic Differentiation, Springer, 2008
Tools:
ADiCape, ADiMat
Theory & Techniques:
Code Optimization, Performance
Mike B. Giles
Collected Matrix Derivative Results for Forward and Reverse Mode Algorithmic Differentiation
Advances in Automatic Differentiation, Springer, 2008
Theory & Techniques:
Hierarchical Approach

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