It is not an easy thing to devote to open-source projects, and your support will help advance open-source ML (especially anomaly and outlier detection). Much appreciated!
Contributions to outlier detection systems, benchmarks, and applications: I build automated, scalable, and accelerated machine learning systems (MLSys) to support large-scale, real-world outlier detection applications in security, finance, and healthcare with millions of downloads. I designed CPU-based (PyOD), GPU-based (TOD), distributed detection systems (SUOD) for tabular (PyOD), time-series (TODS), and graph data (PyGOD). To understand the characteristics of OD algorithms, I co-author large-scale benchmarks for tabular data (ADBench), time-series data (paper), and graph data (UNOD).
4 sponsors have funded yzhao062’s work.
It is a great honor to see you are using my works!!!
Featured work
-
yzhao062/anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
Python 6,359 -
yzhao062/pyod
A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
Python 6,219 -
pygod-team/pygod
A Python Library for Graph Outlier Detection (Anomaly Detection)
Python 645 -
yzhao062/combo
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
Python 593 -
Minqi824/ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark".
Python 312 -
yzhao062/pytod
TOD: GPU-accelerated Outlier Detection via Tensor Operations
Python 112
Get a Sponsor badge on your profile