
[116]
Order by:
[Title],
[Author],
[Editor],
[Year] 

Paul H. Davis, John D. Pryce
A New Implementation of Automatic Differentiation for Use with Numerical Software
School of Mathematics, University of Bristol, 1987 
not yet classified


Mohamed Tadjouddine, Shaun A. Forth, John D. Pryce
AD Tools and Prospects for Optimal AD in CFD Flux Jacobian Calculations
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer,
2002 
Application Area: Computational Fluid Dynamics Tools: AD01, ADIFOR, TAMC


John D. Pryce, John K. Reid
ADO1, a Fortran 90 code for Automatic Differentiation
Rutherford Appleton Laboratory, 1998 
Tools: HSL_AD02


John D. Pryce, Mohamed Tadjouddine
Cheap Jacobians by AD Regarded as Compact LU Factorization
2005 
Theory & Techniques: Code Optimization, Data Flow Analysis, XCountry


J. D. Pryce, Khoshsiar Ghaziani, R. , De Witte, V. , W. Govaerts
Computation of normal form coefficients of cycle bifurcations of maps by algorithmic differentiation
Article in
Mathematics and Computers in Simulation, Elsevier Science Publishers B. V.,
2010 
Tools: CL_MatContM Theory & Techniques: Taylor Arithmetic


Bruce R. Stephens, John D. Pryce
DAPRE: A Differentiation Arithmetic System for FORTRAN
Royal Military College of Science, 1991 
not yet classified


John D. Pryce, Emmanuel M. Tadjouddine
Fast Automatic Differentiation Jacobians by Compact LU Factorization
Article in
SIAM Journal on Scientific Computing, SIAM,
2008 
Theory & Techniques: General


Mohamed Tadjouddine, Shaun A. Forth, John D. Pryce
Hierarchical Automatic Differentiation by Vertex Elimination and Source Transformation
Conference proceeding,
Computational Science and Its Applications  ICCSA 2003, Proceedings of the International Conference on Computational Science and its Applications, Montreal, Canada, May 1821, 2003. Part II, Springer,
2003 
Application Area: Computational Fluid Dynamics Tools: EliAD Theory & Techniques: Hierarchical Approach


John D. Pryce, Nedialko S. Nedialkov, Guangning Tan, Xiao Li
How AD can help solve differentialalgebraic equations
Article in
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis,
2018 
not yet classified


Mohamed Tadjouddine, Frances Bodman, John D. Pryce, Shaun A. Forth
Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation
Automatic Differentiation: Applications, Theory, and Implementations, Springer,
2005 
Tools: EliAD Theory & Techniques: XCountry


Shaun A. Forth, Mohamed Tadjouddine, John D. Pryce, John K. Reid
Jacobian Code Generated by Source Transformation and Vertex Elimination can be as Efficient as HandCoding
Article in
ACM Transactions on Mathematical Software, 2004 
Theory & Techniques: Code Optimization, Data Flow Analysis, XCountry


Bruce R. Stephens, John D. Pryce
Passing functions in Fortran for automatic differentiation
School of Mathematics, University of Bristol, 1987 
not yet classified


Mohamed Tadjouddine, Shaun A. Forth, John D. Pryce, John K. Reid
Performance Issues for Vertex Elimination Methods in Computing Jacobians using Automatic Differentiation
Conference proceeding,
Computational Science  ICCS 2002, Proceedings of the International Conference on Computational Science, Amsterdam, The Netherlands, April 2124, 2002. Part II, Springer,
2002 
Tools: EliAD Theory & Techniques: Code Optimization, Data Flow Analysis, XCountry


Paul H. Davis, John D. Pryce, Bruce Stephens
Recent Developments in Automatic Differentiation
Scientific Software Systems, Chapman and Hall,
1990 
not yet classified


Nedialko S. Nedialkov, John D. Pryce
Solving DifferentialAlgebraic Equations by Taylor Series (I): Computing Taylor Coefficients
Article in
BIT, 2005 
Theory & Techniques: Taylor Arithmetic


John D. Pryce
Solving HighIndex DAEs by Taylor Series
Article in
Numerical Algorithms, 1998 
Theory & Techniques: Taylor Arithmetic

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