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[1-9]
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[Title],
[Author],
[Editor],
[Year] |
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John D. Pryce, John K. Reid
ADO1, a Fortran 90 code for Automatic Differentiation
Rutherford Appleton Laboratory, 1998 |
Tools:
HSL_AD02
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Paul H. Davis, John D. Pryce, Bruce Stephens
Recent Developments in Automatic Differentiation
Scientific Software Systems, Chapman and Hall,
1990 |
not yet classified
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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 21--24, 2002. Part II, Springer,
2002 |
Tools:
EliAD
Theory & Techniques:
Code Optimization, Data Flow Analysis, X-Country
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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:
X-Country
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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 Hand-Coding
Article in
ACM Transactions on Mathematical Software, 2004 |
Theory & Techniques:
Code Optimization, Data Flow Analysis, X-Country
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John D. Pryce, Mohamed Tadjouddine
Cheap Jacobians by AD Regarded as Compact LU Factorization
2005 |
Theory & Techniques:
Code Optimization, Data Flow Analysis, X-Country
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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
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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
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John D. Pryce, Nedialko S. Nedialkov, Guangning Tan, Xiao Li
How AD can help solve differential-algebraic equations
Article in
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis,
2018 |
not yet classified
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