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PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data.
Lof: identifying density-based local outliers
Markus M Breunig, Hans-Peter Kriegel, Raymond T Ng, and Jörg Sander · 2000
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Efficient algorithms for mining outliers from large data sets
Sridhar Ramaswamy, Rajeev Rastogi, and Kyuseok Shim · 2000
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Estimating the support of a high-dimensional distribution
Bernhard Schölkopf, John C Platt, John Shawe-Taylor, Alex J Smola, and Robert C Williamson · 2001
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Fast outlier detection in high dimensional spaces
Fabrizio Angiulli and Clara Pizzuti · 2002
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Discovering cluster-based local outliers
Zengyou He, Xiaofei Xu, and Shengchun Deng · 2003
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Loci: Fast outlier detection using the local correlation integral
Spiros Papadimitriou, Hiroyuki Kitagawa, Phillip B Gibbons, and Christos Faloutsos · 2003
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A novel anomaly detection scheme based on principal component classifier
Mei-Ling Shyu, Shu-Ching Chen, Kanoksri Sarinnapakorn, and LiWu Chang · 2003
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Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator
Johanna Hardin and David M Rocke · 2004
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Feature bagging for outlier detection
Aleksandar Lazarevic and Vipin Kumar · 2005
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One-class support vector machines—an application in machine fault detection and classification
Hyun Joon Shin, Dong-Hwan Eom, and Sung-Shick Kim · 2005
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Angle-based outlier detection in high-dimensional data
Hans-Peter Kriegel, Arthur Zimek, et al · 2008
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Isolation forest
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou · 2008
Cited alongside, same era.
Anomaly-based network intrusion detection: Techniques, systems and challenges
Pedro Garcia-Teodoro, Jesus Diaz-Verdejo, Gabriel Maciá-Fernández, and Enrique Vázquez · 2009
Cited alongside, same era.
Visual evaluation of outlier detection models
Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, and Arthur Zimek · 2010
Cited alongside, same era.
Package ‘outliers’ , 2011
Lukasz Komsta and Maintainer Lukasz Komsta · 2011
Cited alongside, same era.
Interpreting and unifying outlier scores
Hans-Peter Kriegel, Peer Kroger, Erich Schubert, and Arthur Zimek · 2011
Cited alongside, same era.
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, et al · 2011
Cited alongside, same era.
RapidMiner: Data mining use cases and business analytics applications
Markus Hofmann and Ralf Klinkenberg · 2013
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Anomaly detection using autoencoders with nonlinear dimensionality reduction
Mayu Sakurada and Takehisa Yairi · 2014
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Theoretical foundations and algorithms for outlier ensembles
Charu C Aggarwal and Saket Sathe · 2015
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A survey of anomaly detection techniques in financial domain
Mohiuddin Ahmed, Abdun Naser Mahmood, and Md Rafiqul Islam · 2016
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Deep autoencoding models for unsupervised anomaly segmentation in brain mr images
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, and Nassir Navab · 2018
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Pynomaly: Anomaly detection using local outlier probabilities (LoOP)
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Fast and reliable anomaly detection in categorical data
Leman Akoglu, Hanghang Tong, Jilles Vreeken, and Christos Faloutsos · 2012
Cited alongside, same era.
Histogram-based outlier score (HBOS): A fast unsupervised anomaly detection algorithm
Markus Goldstein and Andreas Dengel · 2012
Cited alongside, same era.
Stochastic outlier selection
JHM Janssens, Ferenc Huszár, EO Postma, and HJ van den Herik · 2012
Cited alongside, same era.
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, et al · 2013
Cited alongside, same era.
DCSO: dynamic combination of detector scores for outlier ensembles
Yue Zhao and Maciej K Hryniewicki
Cited in the paper.
XGBOD: improving supervised outlier detection with unsupervised representation learning
Yue Zhao and Maciej K Hryniewicki
Cited in the paper.
Valentino Constantinou · 2018
Later among the works it cites.
Alphaclean: Automatic generation of data cleaning pipelines
Sanjay Krishnan and Eugene Wu · 2019
Closest in time.
Generative adversarial active learning for unsupervised outlier detection
Yezheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang, and Xiangnan He · 2019
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Anomaly detection for an e-commerce pricing system
Jagdish Ramakrishnan, Elham Shaabani, Chao Li, and Mátyás A Sustik · 2019
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LSCP: locally selective combination in parallel outlier ensembles
Yue Zhao, Zain Nasrullah, Maciej K Hryniewicki, and Zheng Li · 2019
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