Showing 1 - 20 of 896

1

PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection
Chen, Sihan ; Qian, Zhuangzhuang ; Siu, Wingchun ; et al.
Companion Proceedings of the ACM on Web Conference 2025. :2807-2810

Conference
2

PyGOD: A Python Library for Graph Outlier Detection.
Kay Liu ; Yingtong Dou ; Xueying Ding ; et al.
Journal of Machine Learning Research. Jan-Dec2024, Vol. 25, p1-9. 9p.

Utility functions Graph neural networks Outlier detection Python programming langu... Sampling (Process)
Academic journal
3

PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection
Chen, Sihan ; Qian, Zhuangzhuang ; Siu, Wingchun ; et al.

Electronic Resource
4

PyOD: A Python Toolbox for Scalable Outlier Detection.
Yue Zhao ; Nasrullah, Zain ; Zheng Li
Journal of Machine Learning Research. 2019, Vol. 20 Issue 85-96, p1-7. 7p.

Maintainability (Enginee... Cointegration Outlier detection Python programming langu... Toolboxes
Academic journal
5

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6

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7

PyGOD: A Python Library for Graph Outlier Detection
Liu, Kay ; Dou, Yingtong ; Ding, Xueying ; et al.

Electronic Resource
9

SEAOP: a statistical ensemble approach for outlier detection in quantitative proteomics data.
Huang, Jinze ; Zhao, Yang ; Meng, Bo ; et al.
Briefings in Bioinformatics. May2024, Vol. 25 Issue 3, p1-14. 14p.

Data structures Quality control Outlier detection Statistical ensembles Proteomics Chi-squared test
Academic journal
10

PyOD: A Python Toolbox for Scalable Outlier Detection
Zhao, Yue ; Nasrullah, Zain ; Li, Zheng ; et al.

Electronic Resource
11

PyGOD: A Python Library for Graph Outlier Detection.
Kay Liu ; Yingtong Dou ; Yue Zhao 0016 ; et al.
CoRR. abs/2204.12095

Academic journal
12

PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning
Li, Yuening ; Zha, Daochen ; Venugopal, Praveen ; et al.
Companion Proceedings of the Web Conference 2020. :153-157

Conference
13

Explain and Monitor Deep Learning Models for Computer Vision using Obz AI
Chung, Neo Christopher ; Binda, Jakub
Proceedings of the 34th ACM International Conference on Information and Knowledge Management. :6624-6628

Conference
15

Unbiased and error-detecting combinatorial pooling experiments with balanced constant-weight Gray codes for consecutive positives detection.
He, Guanchen ; Kovaleva, Vasilisa A ; Barton, Carl ; et al.
Bioinformatics; Dec2025, Vol. 41 Issue 12, p1-9, 9p

GRAY codes COMBINATORIAL designs &... PYTHON programming langu... MATHEMATICAL optimizatio... BIOTECHNOLOGY OPEN source software
Academic journal
16

Seed-Guided, Fault-Aware Horizon Tracking via Greedy Propagation for Geological Modelling.
Brcković, Ana ; Cvetković, Marko ; Kapuralić, Josipa ; et al.
Rudarsko-Geološko-Naftni Zbornik. 2025, Vol. 40 Issue 5, p167-178. 12p.

Geological modeling Petroleum technology Outlier detection Sedimentation & depositi... Three-dimensional imagin... Algorithms
Academic journal
17

A Cluster-Based Filtering Approach to SCADA Data Preprocessing for Wind Turbine Condition Monitoring and Fault Detection.
Kijanowski, Krzysztof ; Barszcz, Tomasz ; Dao, Phong Ba
Energies (19961073); Nov2025, Vol. 18 Issue 22, p5954, 21p

WIND turbines FAULT diagnosis PYTHON programming langu... DATA integrity SUPERVISORY control & da... OUTLIER detection
Academic journal
18
19

Outlier Detection Using Linear Regression in Wind and Solar Integrated Power Systems
Khirwadkar Shukla, Priyanka ; Mahalakshmi, R. ; Angrisani, Leopoldo, Series Editor ; et al.
Advances in Electrical and Computer Technologies : Select Proceedings of ICAECT 2021. 881:1055-1064

eBook
20

Copula-Based Outlier Detection (COPOD)
Feasel, Kevin ; Feasel, Kevin
Finding Ghosts in Your Data : Anomaly Detection Techniques with Examples in Python. :217-228

eBook

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