Armadillo

Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries. (Source: http://freecode.com/)


References in zbMATH (referenced in 33 articles )

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  1. Anthony Ebert, Paul Wu, Kerrie Mengersen, Fabrizio Ruggeri: Computationally Efficient Simulation of Queues: The R Package queuecomputer (2017) arXiv
  2. Brault, Vincent; Chiquet, Julien; Lévy-Leduc, Céline: Efficient block boundaries estimation in block-wise constant matrices: an application to HiC data (2017)
  3. Hafstein, Sigurdur F.; Li, Huijuan: Computation of Lyapunov functions for nonautonomous systems on finite time-intervals by linear programming (2017)
  4. Hunt, Alexander; Surulescu, Christina: A multiscale modeling approach to glioma invasion with therapy (2017)
  5. Pierre Fernique, Christophe Pradal: AutoWIG: Automatic Generation of Python Bindings for C++ Libraries (2017) arXiv
  6. Avanzini, Francesco; Fresch, Barbara; Moro, Giorgio J.: Pilot-wave quantum theory with a single Bohm’s trajectory (2016)
  7. Klibanov, Michael V.; Nguyen, Loc H.; Pan, Kejia: Nanostructures imaging via numerical solution of a 3-D inverse scattering problem without the phase information (2016)
  8. Klibanov, Michael V.; Nguyen, Loc H.; Sullivan, Anders; Nguyen, Lam: A globally convergent numerical method for a 1-d inverse medium problem with experimental data (2016)
  9. Pastorino, Roland; Cosco, Francesco; Naets, Frank; Desmet, Wim; Cuadrado, Javier: Hard real-time multibody simulations using ARM-based embedded systems (2016)
  10. Philip Rinn, Pedro G. Lind, Matthias Waechter, Joachim Peinke: The Langevin Approach: An R Package for Modeling Markov Processes (2016) arXiv
  11. Rupp, Karl; Tillet, Philippe; Rudolf, Florian; Weinbub, Josef; Morhammer, Andreas; Grasser, Tibor; Jüngel, Ansgar; Selberherr, Siegfried: ViennaCL-linear algebra library for multi- and many-core architectures (2016)
  12. Trinath, G.; Babu, V.: On the solution of the Neumann Poisson problem arising from a compact differencing scheme using the full multi-grid method (2016)
  13. Valentin, Julian; Pflüger, Dirk: Hierarchical gradient-based optimization with B-splines on sparse grids (2016)
  14. Xin Liu, Meina Kan, Wanglong Wu, Shiguang Shan, Xilin Chen: VIPLFaceNet: An Open Source Deep Face Recognition SDK (2016) arXiv
  15. Curtis, Frank E.; Que, Xiaocun: A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees (2015)
  16. Giesl, Peter; Hafstein, Sigurdur: Computation and verification of Lyapunov functions (2015)
  17. Rao, Parthib R.; Schaefer, Laura A.: Numerical stability of explicit off-lattice Boltzmann schemes: a comparative study (2015)
  18. Śmigaj, Wojciech; Betcke, Timo; Arridge, Simon; Phillips, Joel; Schweiger, Martin: Solving boundary integral problems with BEM++ (2015)
  19. Daniel Kosiorowski, Zygmunt Zawadzki: DepthProc An R Package for Robust Exploration of Multidimensional Economic Phenomena (2014) arXiv
  20. Giesl, Peter A.; Hafstein, Sigurdur F.: Revised CPA method to compute Lyapunov functions for nonlinear systems (2014)

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