References in zbMATH (referenced in 537 articles )

Showing results 1 to 20 of 537.
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  1. Alex Tritt, Joshua Morris, Joel Hochstetter, R. P. Anderson, James Saunderson, L. D. Turner: Spinsim: a GPU optimized python package for simulating spin-half and spin-one quantum systems (2022) arXiv
  2. Alvaro J. Garcia-Tejedor, Alberto Nogales: GEMA: An open-source Python library for self-organizing-maps (2022) arXiv
  3. Cai, Shang-Rong; Hwang, Feng-Nan: A hybrid-line-and-curve search globalization technique for inexact Newton methods (2022)
  4. Carrano, Eduardo G.; Cruz, Letícia D.; Baptista, Douglas; Camargo, Daniel; Takahashi, Ricardo H. C.: An efficient and fast local search based heuristic for reel management in a production line of oil extraction pipes (2022)
  5. Christoph W. Wagner; Sebastian Semper; Jan Kirchhof: fastmat: Efficient linear transforms in Python (2022) not zbMATH
  6. Gellis, Jason J.; Rangel Smith, Camila; Foley, Robert A.: PyLithics: A Python package for stone tool analysis (2022) not zbMATH
  7. Jung, Jaeho; Jun, Hyungmin; Lee, Phill-Seung: Self-updated four-node finite element using deep learning (2022)
  8. Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu: PyGOD: A Python Library for Graph Outlier Detection (2022) arXiv
  9. Kicki, Piotr; Łakomy, Krzysztof; Lee, Ki Myung Brian: Tuning of extended state observer with neural network-based control performance assessment (2022)
  10. Nikolay Petrov; Vasil Atanasov; Trevor Thompson: Open-Source MUltiple Tests Corrections and FOrmatted Tables Software (MUFOS) (2022) not zbMATH
  11. Tomer Meir, Rom Gutman, Malka Gorfine: PyDTS: A Python Package for Discrete Time Survival Analysis with Competing Risks (2022) arXiv
  12. Uriarte, Carlos; Pardo, David; Omella, Ángel Javier: A finite element based deep learning solver for parametric PDEs (2022)
  13. William E. Carson IV, Austin Talbot, David Carlson: AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models (2022) arXiv
  14. William H. Savran; Maximilian J. Werner; Danijel Schorlemmer; Philip J. Maechling: pyCSEP: A Python Toolkit For Earthquake Forecast Developers (2022) not zbMATH
  15. Yang, Carl; Buluç, Aydın; Owens, John D.: GraphBLAST: a high-performance linear algebra-based graph framework on the GPU (2022)
  16. Zhai, Jianyuan; Boukouvala, Fani: Data-driven spatial branch-and-bound algorithms for box-constrained simulation-based optimization (2022)
  17. Zmurchok, Cole; Holmes, William R.: Biophysical models of PAR cluster transport by cortical flow in \textitC. elegans early embryogenesis (2022)
  18. Adshead, Peter; Lozanov, Kaloian D.; Weiner, Zachary J.: Non-Gaussianity and the induced gravitational wave background (2021)
  19. A. Grant Schissler, Edward J. Bedrick, Alexander D. Knudson, Tomasz J. Kozubowski, Tin Nguyen, Juli Petereit, Walter W. Piegorsch, Duc Tran: Simulating High-Dimensional Multivariate Data using the bigsimr R Package (2021) arXiv
  20. Ahmed Fawzy Gad: PyGAD: An Intuitive Genetic Algorithm Python Library (2021) arXiv

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