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Jacob Vanderplas
Jacob Vanderplas
Verified email at cs.washington.edu - Homepage
Title
Cited by
Cited by
Year
Scikit-learn: Machine learning in Python
F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
the Journal of machine Learning research 12, 2825-2830, 2011
932962011
SciPy 1.0: fundamental algorithms for scientific computing in Python
P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ...
Nature methods 17 (3), 261-272, 2020
271552020
The astropy project: Building an open-science project and status of the v2. 0 core package
AM Price-Whelan, BM Sipőcz, HM Günther, PL Lim, SM Crawford, ...
The Astronomical Journal 156 (3), 123, 2018
79552018
API design for machine learning software: experiences from the scikit-learn project
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2013
34162013
Seaborn: statistical data visualization
ML Waskom
Journal of Open Source Software 6 (60), 3021, 2021
29702021
JAX: composable transformations of Python+ NumPy programs
J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ...
23372018
Understanding the lomb–scargle periodogram
JT VanderPlas
The Astrophysical Journal Supplement Series 236 (1), 16, 2018
10372018
Python data science handbook: Essential tools for working with data
J VanderPlas
" O'Reilly Media, Inc.", 2016
9432016
SciPy 1.0 Contributors
P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ...
Nat. Methods 17 (3), 352, 2020
8842020
Statistics, data mining, and machine learning in astronomy: a practical Python guide for the analysis of survey data
Ž Ivezić, AJ Connolly, JT VanderPlas, A Gray
Princeton University Press, 2014
675*2014
S... Contributors,“SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,”
P Virtanen, R Gommers, TE Oliphant, M Haberland, T Reddy, ...
Nature methods 17 (3), 261-272, 2020
5502020
First-year Sloan Digital Sky Survey-II supernova results: Hubble diagram and cosmological parameters
R Kessler, AC Becker, D Cinabro, J Vanderplas, JA Frieman, J Marriner, ...
The Astrophysical Journal Supplement Series 185 (1), 32, 2009
4622009
Mwaskom/Seaborn: V0. 8.1 (September 2017)
M Waskom, O Botvinnik, D O'Kane, P Hobson, S Lukauskas, ...
Zenodo, 2017
4412017
SNANA: A public software package for supernova analysis
R Kessler, JP Bernstein, D Cinabro, B Dilday, JA Frieman, S Jha, ...
Publications of the Astronomical Society of the Pacific 121 (883), 1028, 2009
3542009
Lsst science book, version 2.0
PA Abell, J Allison, SF Anderson, JR Andrew, JRP Angel, L Armus, ...
arXiv preprint arXiv:0912.0201, 2009
3212009
Periodograms for multiband astronomical time series
JT VanderPlas, Ž Ivezic
The Astrophysical Journal 812 (1), 18, 2015
2862015
Altair: interactive statistical visualizations for Python
J VanderPlas, B Granger, J Heer, D Moritz, K Wongsuphasawat, ...
Journal of open source software 3 (32), 1057, 2018
2212018
Introduction to astroML: Machine learning for astrophysics
J VanderPlas, AJ Connolly, Ž Ivezić, A Gray
2012 conference on intelligent data understanding, 47-54, 2012
2202012
First-year sloan digital sky survey-II (SDSS-II) supernova results: constraints on nonstandard cosmological models
J Sollerman, E Mörtsell, TM Davis, M Blomqvist, B Bassett, AC Becker, ...
The Astrophysical Journal 703 (2), 1374, 2009
1942009
Scikit-learn: Machine learning in Python
F Pedegrosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
Journal of Machine Learning Research 12, 2825-2830, 2011
1692011
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