References in zbMATH (referenced in 93 articles )

Showing results 1 to 20 of 93.
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  1. Abreu, Rafael; Su, Zeming; Kamm, Jochen; Gao, Jinghuai: On the accuracy of the complex-step-finite-difference method (2018)
  2. Goerigk, Marc; Hamacher, Horst W.; Kinscherff, Anika: Ranking robustness and its application to evacuation planning (2018)
  3. Jason Laura; Kelvin Rodriguez; Adam C. Paquette; Evin Dunn: AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data (2018)
  4. Liew, A.; Pagonakis, D.; Van Mele, T.; Block, P.: Load-path optimisation of funicular networks (2018)
  5. Matthews, Devin A.: High-performance tensor contraction without transposition (2018)
  6. Minjie Zhu, Frank McKenna, Michael H. Scott: OpenSeesPy: Python library for the OpenSees finite element framework (2018)
  7. Morra, Gabriele: Pythonic geodynamics. Implementations for fast computing (2018)
  8. Palmer, Geraint I.; Harper, Paul R.; Knight, Vincent A.: Modelling deadlock in open restricted queueing networks (2018)
  9. Phillip Weinberg, Marin Bukov: QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems. Part II: bosons, fermions and higher spins (2018) arXiv
  10. Al-Hinai, Omar; Wheeler, Mary F.; Yotov, Ivan: A generalized mimetic finite difference method and two-point flux schemes over Voronoi diagrams (2017)
  11. Andrew C. Heusser, Kirsten Ziman, Lucy L. W. Owen, Jeremy R. Manning: HyperTools: A Python toolbox for visualizing and manipulating high-dimensional data (2017) arXiv
  12. Benjamin Guedj, Bhargav Srinivasa Desikan: Pycobra: A Python Toolbox for Ensemble Learning and Visualisation (2017) arXiv
  13. Bezanson, Jeff; Edelman, Alan; Karpinski, Stefan; Shah, Viral B.: Julia: a fresh approach to numerical computing (2017)
  14. Bryan W. Weber, Chih-Jen Sung: UConnRCMPy: Python-based data analysis for rapid compression machines (2017) arXiv
  15. Bryan W. Weber, Kyle E. Niemeyer: ChemKED: a human- and machine-readable data standard for chemical kinetics experiments (2017) arXiv
  16. Carmen Moret-Tatay, Daniel Gamermann, Esperanza Navarro-Pardo, Pedro Fernandez de Cordoba: ExGUtils: A python package for statistical analysis with the ex-gaussian probability density (2017) arXiv
  17. Carr, Hamish (ed.); Garth, Christoph (ed.); Weinkauf, Tino (ed.): Topological methods in data analysis and visualization IV. Theory, algorithms, and applications. Selected papers based on the presentations at the TopoInVis workshop, Annweiler, Germany, 2015 (2017)
  18. Chrétien, Stéphane; Darses, Sébastien; Guyeux, Christophe; Clarkson, Paul: On the pinning controllability of complex networks using perturbation theory of extreme singular values. Application to synchronisation in power grids (2017)
  19. Douglas De Rizzo Meneghetti, Plinio Thomaz Aquino Junior: Computerized Adaptive Testing Simulation Through the Package catsim (2017) arXiv
  20. Lema^ıtre, Guillaume; Nogueira, Fernando; Aridas, Christos K.: Imbalanced-learn: a python toolbox to tackle the curse of imbalanced datasets in machine learning (2017)

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