Citations & Achievements#
Citing PyOD#
PyOD paper is published in JMLR (machine learning open-source software track). If you use PyOD in a scientific publication, we would appreciate citations to the following paper:
@article{zhao2019pyod,
author = {Zhao, Yue and Nasrullah, Zain and Li, Zheng},
title = {PyOD: A Python Toolbox for Scalable Outlier Detection},
journal = {Journal of Machine Learning Research},
year = {2019},
volume = {20},
number = {96},
pages = {1-7},
url = {http://jmlr.org/papers/v20/19-011.html}
}
or:
Zhao, Y., Nasrullah, Z. and Li, Z., 2019. PyOD: A Python Toolbox for Scalable Outlier Detection. Journal of machine learning research (JMLR), 20(96), pp.1-7.
Scientific Work Using or Referencing PyOD#
We are appreciated that PyOD has been increasingly referred and cited in scientific works. Since its release, PyOD has been used in hundred of academic projects. See an incomplete list here.
Featured Posts & Achievements#
PyOD has been well acknowledged by the machine learning community with a few featured posts and tutorials.
Analytics Vidhya: An Awesome Tutorial to Learn Outlier Detection in Python using PyOD Library
KDnuggets: Intuitive Visualization of Outlier Detection Methods
KDnuggets: An Overview of Outlier Detection Methods from PyOD
Towards Data Science: Anomaly Detection for Dummies
Computer Vision News (March 2019): Python Open Source Toolbox for Outlier Detection
FLOYDHUB: Introduction to Anomaly Detection in Python
awesome-machine-learning: General-Purpose Machine Learning
Lecture on anomaly detection with PyOD by Dr.Hadi Fanaee: Anomaly Detection Lecture
Workshop/Showcase using PyOD:
Detecting the Unexpected: An Introduction to Anomaly Detection Methods, KISS Technosignatures Workshop by Dr. Kiri Wagstaff @ Jet Propulsion Laboratory, California Institute of Technology. [Workshop Video] [PDF]
GitHub Python Trending:
2019: Jul 8th-9th, Apr 5th-6th, Feb 10th-11th, Jan 23th-24th, Jan 10th-14th
2018: Jun 15, Dec 8th-9th
Miscellaneous: