References in zbMATH (referenced in 113 articles , 1 standard article )

Showing results 1 to 20 of 113.
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  1. Banović, Mladen; Mykhaskiv, Orest; Auriemma, Salvatore; Walther, Andrea; Legrand, Herve; Müller, Jens-Dominik: Algorithmic differentiation of the Open CASCADE technology CAD kernel and its coupling with an adjoint CFD solver (2018)
  2. Baydin, Atılım Güneş; Pearlmutter, Barak A.; Radul, Alexey Andreyevich; Siskind, Jeffrey Mark: Automatic differentiation in machine learning: a survey (2018)
  3. Bissuel, Aloïs; Allaire, Grégoire; Daumas, Laurent; Barré, Sébastien; Rey, Floriane: Linearized Navier-Stokes equations for aeroacoustics using stabilized finite elements: boundary conditions and industrial application to aft-Fan noise propagation (2018)
  4. Cots, Olivier; Gergaud, Joseph; Goubinat, Damien: Direct and indirect methods in optimal control with state constraints and the climbing trajectory of an aircraft (2018)
  5. Hascoët, Laurent; Morlighem, M.: Source-to-source adjoint algorithmic differentiation of an ice sheet model written in C (2018)
  6. Jiang, Ting; Zhou, XiaoJian: Gradient/Hessian-enhanced least square support vector regression (2018)
  7. Pascual, Valérie; Hascoët, Laurent: Mixed-language automatic differentiation (2018)
  8. Rodrigues, S. S.; Marta, A. C.: Adjoint formulation of a steady multistage turbomachinery interface using automatic differentiation (2018)
  9. Römer, Ulrich; Narayanamurthi, Mahesh; Sandu, Adrian: Solving parameter estimation problems with discrete adjoint exponential integrators (2018)
  10. Shi-Dong, Doug; Nadarajah, Siva: Approximate Hessian for accelerated convergence of aerodynamic shape optimization problems in an adjoint-based framework (2018)
  11. Siskind, Jeffrey Mark; Pearlmutter, Barak A.: Divide-and-conquer checkpointing for arbitrary programs with no user annotation (2018)
  12. Srajer, Filip; Kukelova, Zuzana; Fitzgibbon, Andrew: A benchmark of selected algorithmic differentiation tools on some problems in computer vision and machine learning (2018)
  13. Towara, M.; Naumann, U.: SIMPLE adjoint message passing (2018)
  14. Zhou, Beckett Y.; Ryong Koh, Seong; Gauger, Nicolas R.; Meinke, Matthias; Schöder, Wolfgang: A discrete adjoint framework for trailing-edge noise minimization via porous material (2018)
  15. Auroux, D.; Groza, V.: Optimal parameters identification and sensitivity study for abrasive waterjet milling model (2017)
  16. Geeraert, Sébastien; Lehalle, Charles-Albert; Pearlmutter, Barak A.; Pironneau, Olivier; Reghai, Adil: Mini-symposium on automatic differentiation and its applications in the financial industry (2017)
  17. Hückelheim, Jan Christian; Hascoët, Laurent; Müller, Jens-Dominik: Algorithmic differentiation of code with multiple context-specific activities (2017)
  18. Mohammadi, Bijan: Uncertainty quantification in littoral erosion (2017)
  19. Tranquilli, Paul; Glandon, S. Ross; Sarshar, Arash; Sandu, Adrian: Analytical Jacobian-vector products for the matrix-free time integration of partial differential equations (2017)
  20. Auroux, Didier; Groza, Vladimir: Sensitivity studies and parameters identification for noisy 3D moving AWJM model (2016)

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