www.Autodiff.org - Publication Database

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[1-20] [21-32]

Order by: [Title], [Author], [Editor], [Year]
	Bruce Christianson A Leibniz Notation for Automatic Differentiation Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: General
	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
	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
	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
	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
	James A. Reed, Jean Utke, Hany S. Abdel-Khalik Combining Automatic Differentiation Methods for High-Dimensional Nonlinear Models Recent Advances in Algorithmic Differentiation, Springer, 2012	Application Area: Uncertainty Analysis Tools: OpenAD, Rapsodia Theory & Techniques: Higher Order, Reverse Mode
	Kshitij Kulshreshtha, Jan Marburger Computing Derivatives in a Meshless Simulation Using Permutations in ADOL-C Recent Advances in Algorithmic Differentiation, Springer, 2012	Tools: ADOL-C
	David C. Carothers, Stephen K. Lucas, G. Edgar Parker, Joseph D. Rudmin, James S. Sochacki, Roger J. Thelwell, Anthony Tongen, Paul G. Warne Connections Between Power Series Methods and Automatic Differentiation Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: General
	Peder A. Olsen, Steven J. Rennie, Vaibhava Goel Efficient Automatic Differentiation of Matrix Functions Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Hierarchical Approach
	Eric Phipps, Roger Pawlowski Efficient Expression Templates for Operator Overloading-Based Automatic Differentiation Recent Advances in Algorithmic Differentiation, Springer, 2012	Tools: Sacado Theory & Techniques: Code Optimization
	Kamil A. Khan, Paul I. Barton Evaluating an Element of the Clarke Generalized Jacobian of a Piecewise Differentiable Function Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Generalized Jacobian
	Benjamin Letschert, Kshitij Kulshreshtha, Andrea Walther, Duc Nguyen, Assefaw Gebremedhin, Alex Pothen Exploiting Sparsity in Automatic Differentiation on Multicore Architectures Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Parallelism, Sparsity
	Marco Nehmeier Generative Programming for Automatic Differentiation Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Code Optimization
	Johannes Lotz, Uwe Naumann, Jörn Ungermann Hierarchical Algorithmic Differentiation A Case Study Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Hierarchical Approach
	Ahmad Bani Younes, James Turner, Manoranjan Majji, John Junkins High-Order Uncertainty Propagation Enabled by Computational Differentiation Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: Higher Order, Uncertainties
	Sri Hari Krishna Narayanan, Boyana Norris, Paul Hovland, Assefaw Gebremedhin Implementation of Partial Separability in a Source-to-Source Transformation AD Tool Recent Advances in Algorithmic Differentiation, Springer, 2012	Theory & Techniques: partial separability

[1-20] [21-32]

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