References in zbMATH (referenced in 210 articles )

Showing results 1 to 20 of 210.
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  1. Amir M. Mir; Jalal A. Nasiri: LightTwinSVM: A Simple and Fast Implementation of Standard Twin Support Vector Machine Classifier (2019) not zbMATH
  2. Andrei V. Novikov: PyClustering: Data Mining Library (2019) not zbMATH
  3. Andrew Abi-Mansour: PyGran: An object-oriented library for DEM simulation and analysis (2019) not zbMATH
  4. Benjamin W. L. Margolis, Kenneth R. Lyons: ndsplines: A Python Library for Tensor-Product B-Splines of Arbitrary Dimension (2019) not zbMATH
  5. Blaise J. Thompson; Kyle F. Sunden; Darien J. Morrow; Daniel D. Kohler; John C. Wright: WrightTools: a Python package for multidimensional spectroscopy (2019) not zbMATH
  6. Carrillo, José Antonio; Craig, Katy; Patacchini, Francesco S.: A blob method for diffusion (2019)
  7. Christopher Hahne; Amar Aggoun: PlenoptiSign: An optical design tool for plenoptic imaging (2019) not zbMATH
  8. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in python using sfepy (2019)
  9. Danny C. Price, J. Emilio Enriquez, Yuhong Chen, Mark Siebert: Blimpy: Breakthrough Listen I/O Methods for Python (2019) not zbMATH
  10. Davide Micieli, Triestino Minniti, Giuseppe Gorini: NeuTomPy toolbox, a Python package for tomographic data processing and reconstruction (2019) not zbMATH
  11. De Loera, Jesús A.; Petrović, Sonja; Silverstein, Lily; Stasi, Despina; Wilburne, Dane: Random monomial ideals (2019)
  12. D. Huppenkothen, M. Bachetti, A. L. Stevens, S. Migliari, P. Balm, O. Hammad, U. M. Khan, H. Mishra, H. Rashid, S. Sharma, R. V. Blanco, E. M. Ribeiro: Stingray: A Modern Python Library For Spectral Timing (2019) arXiv
  13. Dudziuk, Grzegorz; Lachowicz, Mirosław; Leszczyński, Henryk; Szymańska, Zuzanna: A simple model of collagen remodeling (2019)
  14. Eric W. Koch, Ryan D. Boyden, Blakesley Burkhart, Adam Ginsburg, Jason L. Loeppky, Stella S.R. Offner: TurbuStat: Turbulence Statistics in Python (2019) arXiv
  15. Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke: ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions (2019) arXiv
  16. Gevorkyan, Migran N.; Korolkova, Anna V.; Kulyabov, Dmitry S.; Lovetskiy, Konstantin P.: Statistically significant comparative performance testing of Julia and Fortran languages in case of Runge-Kutta methods (2019)
  17. Jeffrey S. Hazboun, Joseph D. Romano, Tristan L. Smith: Hasasia: A Python package for Pulsar Timing Array Sensitivity Curves (2019) not zbMATH
  18. Johansson, Robert: Numerical Python. Scientific computing and data science applications with Numpy, SciPy and Matplotlib (2019)
  19. Jonas Fassbender: libconform v0.1.0: a Python library for conformal prediction (2019) arXiv
  20. Keskar, N.; Wächter, Andreas: A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization (2019)

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