References in zbMATH (referenced in 144 articles )

Showing results 1 to 20 of 144.
Sorted by year (citations)

1 2 3 ... 6 7 8 next

  1. De Loera, Jesús A.; Petrović, Sonja; Silverstein, Lily; Stasi, Despina; Wilburne, Dane: Random monomial ideals (2019)
  2. Keskar, N.; Wächter, Andreas: A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization (2019)
  3. Michael Slugocki , Allison B. Sekuler, Patrick Bennett: BayesFit: A tool for modeling psychophysical data using Bayesian inference (2019) not zbMATH
  4. Abreu, Rafael; Su, Zeming; Kamm, Jochen; Gao, Jinghuai: On the accuracy of the complex-step-finite-difference method (2018)
  5. Adrian Bevan, Thomas Charman, Jonathan Hays: HIPSTER - A python package for particle physics analyses (2018) arXiv
  6. Andrew Beers; James Brown; Ken Chang; Katharina Hoebel; Elizabeth Gerstner; Bruce Rosen; Jayashree Kalpathy-Cramer: DeepNeuro: an open-source deep learning toolbox for neuroimaging (2018) arXiv
  7. Ashwin Vishnu Mohanan; Cyrille Bonamy; Miguel Calpe Linares; Pierre Augier: FluidSim: modular, object-oriented Python package for high-performance CFD simulations (2018) arXiv
  8. Bánhelyi, Balázs; Csendes, Tibor; Lévai, Balázs; Pál, László; Zombori, Dániel: The GLOBAL optimization algorithm. Newly updated with Java implementation and parallelization (2018)
  9. Benyuan Liu; Bin Yang; Canhua Xu; Junying Xia; Meng Dai; Zhenyu Ji; Fusheng You; Xiuzhen Dong; Xuetao Shi; Feng Fu: pyEIT: A python based framework for Electrical Impedance Tomography (2018) not zbMATH
  10. Bisotti, M.-A., Cortés-Ortuño, D., Pepper, R., Wang, W., Beg, M., Kluyver, T., Fangohr, H.: Fidimag - A Finite Difference Atomistic and Micromagnetic Simulation Package (2018) not zbMATH
  11. Brendon Brewer; Daniel Foreman-Mackey: DNest4: Diffusive Nested Sampling in C++ and Python (2018) not zbMATH
  12. Catherine Zucker; Hope How-Huan Chen: RadFil: a Python Package for Building and Fitting Radial Profiles for Interstellar Filaments (2018) arXiv
  13. Collin J. Wilkinson, Yihong Z. Mauro, John C. Mauro: RelaxPy: Python code for modeling of glass relaxation behavior (2018) not zbMATH
  14. Daniel M. Faes: Use of Python programming language in astronomy and science (2018) arXiv
  15. D.M. Straub: flavio: a Python package for flavour and precision phenomenology in the Standard Model and beyond (2018) arXiv
  16. Fischer, Thomas; Krauss, Christopher: Deep learning with long short-term memory networks for financial market predictions (2018)
  17. Garcia, D.; Ghommem, M.; Collier, N.; Varga, B. O. N.; Calo, V. M.: PyFly: a fast, portable aerodynamics simulator (2018)
  18. Goerigk, Marc; Hamacher, Horst W.; Kinscherff, Anika: Ranking robustness and its application to evacuation planning (2018)
  19. Guedj, Benjamin; Desikan, Bhargav Srinivasa: Pycobra: a Python toolbox for ensemble learning and visualisation (2018)
  20. Guillaume Baudart, Martin Hirzel, Kiran Kate, Louis Mandel, Avraham Shinnar: Yaps: Python Frontend to Stan (2018) arXiv

1 2 3 ... 6 7 8 next