Scikit-learn: Machine Learning in Python. - Fabian Pedregosa; Gaël Varoquaux; Alexandre Gramfort; Vincent Michel; Bertrand Thirion; Olivier Grisel; Mathieu Blondel; Peter Prettenhofer; Ron Weiss; Vincent Dubourg; Jake VanderPlas; Alexandre Passos; et al. (J. Mach. Learn. Res., 2011)

Hierarchical Probabilistic Models for Group Anomaly Detection. - Liang Xiong; Barnabás Póczos; Jeff G. Schneider; Andrew J. Connolly; Jake VanderPlas (AISTATS, 2011)

Introduction to astroML: Machine learning for astrophysics. - Jacob VanderPlas; Andrew J. Connolly; Zeljko Ivezic; Alexander G. Gray (CIDU, 2012)

API design for machine learning software: experiences from the scikit-learn project. - Lars Buitinck; Gilles Louppe; Mathieu Blondel; Fabian Pedregosa; Andreas Mueller; Olivier Grisel; Vlad Niculae; Peter Prettenhofer; Alexandre Gramfort; Jaques Grobler; Robert Layton; Jake VanderPlas; et al. (CoRR, 2013)

Squeezing a Big Orange into Little Boxes: The AscotDB System for Parallel Processing of Data on a Sphere. - Jacob VanderPlas; Emad Soroush; K. Simon Krughoff; Magdalena Balazinska (IEEE Data Eng. Bull., 2013)

A Demonstration of Iterative Parallel Array Processing in Support of Telescope Image Analysis. - Matthew I. Moyers; Emad Soroush; Spencer Wallace; K. Simon Krughoff; Jake VanderPlas; Magdalena Balazinska; Andrew J. Connolly (Proc. VLDB Endow., 2013)

Frequentism and Bayesianism: A Python-driven Primer. - Jake VanderPlas (SciPy, 2014)

megaman: Manifold Learning with Millions of points. - James McQueen; Marina Meila; Jacob VanderPlas; Zhongyue Zhang (CoRR, 2016)

Megaman: Scalable Manifold Learning in Python. - James McQueen; Marina Meila; Jacob VanderPlas; Zhongyue Zhang (J. Mach. Learn. Res., 2016)

mst_clustering: Clustering via Euclidean Minimum Spanning Trees. - Jake VanderPlas (J. Open Source Softw., 2016)

Hack Weeks as a model for Data Science Education and Collaboration. - Daniela Huppenkothen; Anthony Arendt; David W. Hogg; Karthik Ram; Jake VanderPlas; Ariel Rokem (CoRR, 2017)

Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads. - Parmita Mehta; Sven Dorkenwald; Dongfang Zhao 001; Tomer Kaftan; Alvin Cheung; Magdalena Balazinska; Ariel Rokem; Andrew J. Connolly; Jacob VanderPlas; Yusra AlSayyad (Proc. VLDB Endow., 2017)

From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning. - Juan B. Cabral; Bruno Sánchez; Felipe Ramos; Sebastián Gurovich; Pablo M. Granitto; Jacob VanderPlas (Astron. Comput., 2018)

approxposterior: Approximate Posterior Distributions in Python. - David P. Fleming; Jake VanderPlas (J. Open Source Softw., 2018)

Altair: Interactive Statistical Visualizations for Python. - Jacob VanderPlas; Brian E. Granger; Jeffrey Heer; Dominik Moritz; Kanit Wongsuphasawat; Arvind Satyanarayan; Eitan Lees; Ilia Timofeev; Ben Welsh; Scott Sievert (J. Open Source Softw., 2018)

Journal of Open Source Software (JOSS): design and first-year review. - Arfon M. Smith; Kyle E. Niemeyer; Daniel S. Katz; Lorena A. Barba; George Githinji; Melissa Gymrek; Kathryn D. Huff; Christopher R. Madan; Abigail Cabunoc Mayes; Kevin M. Moerman; Pjotr Prins; Karthik Ram; et al. (PeerJ Comput. Sci., 2018)

Altair: Declarative statistical visualization library for Python. - Jacob VanderPlas; Brian E. Granger; Jeffrey Heer; Dominik Moritz; Kanit Wongsuphasawat; Eitan Lees; Ilia Timofeev; Ben Welsh; Scott Sievert (Zenodo, 2018)

Altair: Declarative statistical visualization library for Python. - Jacob VanderPlas; Brian E. Granger; Jeffrey Heer; Dominik Moritz; Kanit Wongsuphasawat; Arvind Satyanarayan; Eitan Lees; Ilia Timofeev; Ben Welsh; Scott Sievert (Zenodo, 2018)

SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python. - Pauli Virtanen; Ralf Gommers; Travis E. Oliphant; Matt Haberland; Tyler Reddy; David Cournapeau; Evgeni Burovski; Pearu Peterson; Warren Weckesser; Jonathan Bright; Stéfan van der Walt; Matthew Brett; et al. (CoRR, 2019)

Applying Information Theory to Design Optimal Filters for Photometric Redshifts. - J. Bryce Kalmbach; Jacob VanderPlas; Andrew J. Connolly (CoRR, 2020)