References in zbMATH (referenced in 1221 articles , 1 standard article )

Showing results 1 to 20 of 1221.
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  1. Aliverti, Emanuele; Russo, Massimiliano: Stratified stochastic variational inference for high-dimensional network factor model (2022)
  2. Antonietti, P. F.; Manuzzi, E.: Refinement of polygonal grids using convolutional neural networks with applications to polygonal discontinuous Galerkin and virtual element methods (2022)
  3. Bai, Fang; Bartoli, Adrien: Procrustes analysis with deformations: a closed-form solution by eigenvalue decomposition (2022)
  4. Bajārs, Jānis; Kozirevs, Filips: Data-driven intrinsic localized mode detection and classification in one-dimensional crystal lattice model (2022)
  5. Beck, Amir; Sharon, Raz: New results on multi-dimensional linear discriminant analysis (2022)
  6. Belcaid, A.; Belkbir, H.: Constrained energy variation for change point detection (2022)
  7. Belov, A. V.; Gvishiani, A. D.; Getmanov, V. G.; Kovylyaeva, A. A.; Soloviev, A. A.; Chinkin, V. E.; Yanke, V. G.; Yashin, I. I.: Recognition of geomagnetic storm based on neural network model estimates of Dst indices (2022)
  8. Benfenati, Alessandro; Borghi, Giacomo; Pareschi, Lorenzo: Binary interaction methods for high dimensional global optimization and machine learning (2022)
  9. Ben Hassan Saïdi, Ismaïl; Schmelzer, Martin; Cinnella, Paola; Grasso, Francesco: CFD-driven symbolic identification of algebraic Reynolds-stress models (2022)
  10. Botsas, Themistoklis; Mason, Lachlan R.; Pan, Indranil: Rule-based Bayesian regression (2022)
  11. Boudabsa, Lotfi; Filipović, Damir: Machine learning with kernels for portfolio valuation and risk management (2022)
  12. Burridge, James; Gnacik, Michał: Public efforts to reduce disease transmission implied from a spatial game (2022)
  13. Chandna, Akshat; Srinivasan, Sanjay: Mapping natural fracture networks using geomechanical inferences from machine learning approaches (2022)
  14. Chen, Jie; Saad, Yousef; Zhang, Zechen: Graph coarsening: from scientific computing to machine learning (2022)
  15. Costa, Gianni; Ortale, Riccardo: Hierarchical Bayesian text modeling for the unsupervised joint analysis of latent topics and semantic clusters (2022)
  16. Dai, Wei; Jin, Baisuo: Bayesian inference of clustering and multiple Gaussian graphical models selection (2022)
  17. Fanaskov, Vladimir: Gaussian belief propagation solvers for nonsymmetric systems of linear equations (2022)
  18. Fraccaroli, Michele; Lamma, Evelina; Riguzzi, Fabrizio: Symbolic DNN-tuner (2022)
  19. Gahm, Christian; Uzunoglu, Aykut; Wahl, Stefan; Ganschinietz, Chantal; Tuma, Axel: Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning (2022)
  20. Gao, Can; Wang, Zhicheng; Zhou, Jie: Three-way approximate reduct based on information-theoretic measure (2022)

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