References in zbMATH (referenced in 31 articles , 1 standard article )

Showing results 1 to 20 of 31.
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  1. Burgard, Jan Pablo; Krause, Joscha; Schmaus, Simon: Estimation of regional transition probabilities for spatial dynamic microsimulations from survey data lacking in regional detail (2021)
  2. Hinz, Jochen; Jaeschke, Andrzej; Möller, Matthias; Vuik, Cornelis: The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications (2021)
  3. Iiduka, Hideaki: Inexact stochastic subgradient projection method for stochastic equilibrium problems with nonmonotone bifunctions: application to expected risk minimization in machine learning (2021)
  4. Manson, Jamie A.; Chamberlain, Thomas W.; Bourne, Richard A.: MVMOO: mixed variable multi-objective optimisation (2021)
  5. Zhang, Jin; Wang, Cong; Chen, Guoqing: A review selection method for finding an informative subset from online reviews (2021)
  6. D’Amico, Guglielmo; De Blasis, Riccardo: A multivariate Markov chain stock model (2020)
  7. De Blasis, Riccardo: The price leadership share: a new measure of price discovery in financial markets (2020)
  8. Gavrikova, N. M.; Golubev, Yu. F.: Using a three-impulse maneuvering scheme for returning from the lunar orbit to the reentry point of the Earth’s atmosphere (2020)
  9. Grymin, Radosław; Bożejko, Wojciech; Chaczko, Zenon; Pempera, Jarosław; Wodecki, Mieczysław: Algorithm for solving the discrete-continuous inspection problem (2020)
  10. Hinz, Jochen; Helmig, Jan; Möller, Matthias; Elgeti, Stefanie: Boundary-conforming finite element methods for twin-screw extruders using spline-based parameterization techniques (2020)
  11. Popkov, Y. S.; Popkov, A. Y.; Dubnov, Y. A.: Cross-entropy reduction of data matrix with restriction on information capacity of projectors and their norms (2020)
  12. Wu, N., Kenway, G., Mader, C. A., Jasa, J., Martins, J. R. R. A.: pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems (2020) not zbMATH
  13. Chen, Guodong; Fidkowski, Krzysztof J.: Discretization error control for constrained aerodynamic shape optimization (2019)
  14. Hirschler, T.; Bouclier, R.; Duval, A.; Elguedj, T.; Morlier, J.: The embedded isogeometric Kirchhoff-Love shell: from design to shape optimization of non-conforming stiffened multipatch structures (2019)
  15. Kord, Ali; Capecelatro, Jesse: Optimal perturbations for controlling the growth of a Rayleigh-Taylor instability (2019)
  16. Schweidtmann, Artur M.; Mitsos, Alexander: Deterministic global optimization with artificial neural networks embedded (2019)
  17. Dubreuil, S.; Bartoli, N.; Gogu, C.; Lefebvre, T.; Colomer, J. Mas: Extreme value oriented random field discretization based on an hybrid polynomial chaos expansion -- Kriging approach (2018)
  18. Endres, Stefan C.; Sandrock, Carl; Focke, Walter W.: A simplicial homology algorithm for Lipschitz optimisation (2018)
  19. Estévez Schwarz, Diana; Lamour, René: A new approach for computing consistent initial values and Taylor coefficients for DAEs using projector-based constrained optimization (2018)
  20. Mai, Vinh Q.; Vo, Tuoi T.; Meere, Martin: Modelling hyaluronan degradation by Streptococcus pneumoniae hyaluronate lyase (2018)

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