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Showing 1 to 12 of 12 for “"algorithmic differentiation"”.

  1. Algorithmic differentiation of Java programs

    Slusanschi, Emil-IoanPublikationsserver der RWTH Aachen University2008

    … used to obtain computer derivatives is Automatic Differentiation (AD). The fact that to date no usable AD tool implementation exists for Java motivated the development of an AD tool for the Java language. Because of the portability and simplicity in terms of standardization provided by the Java …

    aachen Repository record

  2. Adjoint Venture: Fast Greeks with Adjoint Algorithmic Differentiation

    McPetrie, Christopher LindsayDivision of Actuarial Science2017

    … ideas are extended to the paradigm of Adjoint Algorithmic Differentiation, and it is illustrated how the use of sophisticated techniques within this space can further improve the ease of use and efficiency of sensitivity calculations.

    cape-town Repository record

  3. Accelerated Adjoint Algorithmic Differentiation with Applications in Finance

    De Beer, JarredDivision of Actuarial Science2017

    Adjoint Differentiation's (AD) ability to calculate Greeks efficiently and to machine precision while scaling in constant time to the number of input variables is attractive for calibration and hedging where frequent calculations are required. Algorithmic adjoint differentiation tools automatically …

    cape-town Repository record

  4. Multi-parameter estimation in glacier models with adjoint and algorithmic differentiation

    Davis, Andrew D. (Andrew Donaldson)Massachusetts Institute of Technology2012

    … and often require discretizing additional PDE's. Algorithmic differentiation (AD) decomposes the model into a composite of elementary operations (+, -, *, /, etc ... ) and a source-to-source transformation generates code for the Jacobian and its transpose for each operations. Derivatives computed …

    mit Repository record

  5. A Modular Framework for Generation and Maintenance of Adjoint Solvers Assisted by Algorithmic Differentiation - with Applications to an Incompressible Navier-Stokes Solver

    Auvinen, MikkoAalto University2014

    … This methodology hinges upon exposing the algorithmic structure of the original solver to the formulation of the adjoint problem. The process yields a corresponding algorithmic description for the adjoint solver, which is subsequently assembled utilizing a library of reverse mode …

    aalto Repository record

  6. Multi-CubeSat mission planning enabled through parallel computing

    Ghosh, AlexanderUniversity of Illinois at Urbana-Champaign2013

    … and Jacobian are developed in real time using algorithmic differentiation, which allows for significantly higher accuracy over traditional finite difference methods. This framework is tested against analytical methods developed by Wiesel for in-plane, and Edelbaum and Kechichian for out of …

    uiuc Repository record

  7. THE THEORY OF COMBINATORY DIFFERENTIATION AND LOCALITY IN QUANTUM CHEMISTRY

    Li, KangboCornell University2024

    … Chapter one is the theory of combinatory differentiation, which practically brings symbolic differentiation up to speed with algorithmic differentiation and enables the analytic automation of the backpropagation and differential tensor calculus. At the center of this model of …

    cornell Repository record

  8. Geometric numerical integration for optimisation

    Riis, Erlend SkaldehaugUniversity of Cambridge2019

    … parameter-dependent solution mapping, and study algorithmic differentiation approaches to evaluating the derivatives. Furthermore, we prove that the algorithmic derivatives converge to the implicit derivatives. Thus we demonstrate that, although some parameter tuning problems must inevitably be …

    cambridge Repository record

  9. Uncertainty quantification in ocean state estimation

    Kalmikov, Alexander G.Massachusetts Institute of Technology and Woods Hole Oceanographic Institution2013

    … model (MITgcm) are generated by means of algorithmic differentiation (AD). Computational complexity of the Hessian code is reduced by tangent linear differentiation of the adjoint code, which preserves the speedup of adjoint checkpointing schemes in the second derivative calculation. A …

    woods-hole Repository record

  10. Uncertainty Quantification in ocean state estimation

    Kalmikov, Alexander GMassachusetts Institute of Technology2013

    … model (MITgcm) are generated by means of algorithmic differentiation (AD). Computational complexity of the Hessian code is reduced by tangent linear differentiation of the adjoint code, which preserves the speedup of adjoint checkpointing schemes in the second derivative calculation. A …

    mit Repository record

  11. On the efficient determination of Hessian matrix sparsity pattern : algorithms and data structures

    Sultana, Marzia, University of Lethbridge. Faculty of Arts and Science2016

    lethbridge

  12. Parallel reversal schedules using more checkpoints than processors

    Diels-Grabsch, VolkerHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät2015

    Parallele Umkehr-Ablaufpläne (Parallel reversal schedules) beschreiben, wie die Zustände eines evolutionären Systems, etwa einer atmosphärischen oder ozeanographischen Simulation, in umgekehrter Reihenfolge berechnet werden können, ohne dass alle Zustände im Speicher gehalten werden müssen. Auf …

    humboldt-diss Repository record