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As computational challenges in optimization and statistical inference grow ever harder, algorithms that utilize derivatives are becoming increasingly more important.
Hybrid Monte Carlo
Duane, A., Kennedy, A., Pendleton, B., and Roweth, D. (1987) · 1987
Earlier work this paper cites.
Generation of finite difference formulas on arbitrarily spaced grids
Fornberg, B. (1988) · 1988
Earlier work this paper cites.
The Design and Evolution of C++
Stroustrup, B. (1994) · 1994
Earlier work this paper cites.
CVODE, a stiff/nonstiff ODE solver in C
Cohen, S. D. and Hindmarsh, A. C. (1996) · 1996
Earlier work this paper cites.
Matrix Computations
Golub, G. H. and Van Loan, C. F. (1996) · 1996
Earlier work this paper cites.
The Art of Computer Programming, Volume 1, Fundamental Algorithms
Knuth, D. E. (1997) · 1997
Earlier work this paper cites.
Pimpls—beauty marks you can depend on
Sutter, H. (1998) · 1998
Earlier work this paper cites.
Language support for regions
Gay, D. and Aiken, A. (2001) · 2001
Earlier work this paper cites.
More Exceptional C++
Sutter, H. (2001) · 2001
Earlier work this paper cites.
Accuracy and Stability of Numerical Algorithms
Higham, N. J. (2002) · 2002
Earlier work this paper cites.
C++ Templates: The Complete Guide
Vandevoorde, D. and Josuttis, N. M. (2002) · 2002
Earlier work this paper cites.
International Standard ISO/IEC 14882: Programming languages—C++
International Standardization Organization (2003) · 2003
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Semiautomatic differentiation for efficient gradient computations
Gay, D. M. (2005) · 2005
Cited alongside, same era.
An overview of the Trilinos project
Heroux, M. A., Bartlett, R. A., Howle, V. E., Hoekstra, R. J., Hu, J. J., Kolda, T. G., Lehoucq, R. B., Long, K. R., Pawlowski, R. P., Phipps, E. T., Salinger, A. G., Thornquist, H. K., Tuminaro, R. S., Willenbring, J. M., Williams, A., and Stanley, K. S. (2005) · 2005
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SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers
Hindmarsh, A. C., Brown, P. N., Grant, K. E., Lee, S. L., Serban, R., Shumaker, D. E., and Woodward, C. S. (2005) · 2005
Cited alongside, same era.
Matrix Differential Calculus with Applications in Statistics and Econometrics
Magnus, J. R. and Neudecker, H. (2007) · 2007
Cited alongside, same era.
Numerical Recipes in C++
CppAD: a package for C++ algorithmic differentiation
Bell, B. M. (2012) · 2012
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The matrix cookbook
Petersen, K. B. and Pedersen, M. S. (2012) · 2012
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Bayesian Data Analysis
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013) · 2013
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The Tapenade automatic differentiation tool: principles, model, and specification
Hascoët, L. and Pascual, V. (2013) · 2013
Later among the works it cites.
odeint: Solving ODEs in C++
Ahnert, K. and Mulansky, M. (2014) · 2014
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The geometric foundations of Hamiltonian Monte Carlo
Betancourt, M., Byrne, S., Livingstone, S., and Girolami, M. (2014) · 2014
Later among the works it cites.
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Cited alongside, same era.
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SymPy: Python library for symbolic mathematics
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Weber, S., Carpenter, B., Lee, D., Bois, F. Y., Gelman, A., and Racine, A. (2014) · 2014
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Wolfram Research, Inc. (2014) · 2014
Later among the works it cites.