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Anomaly detection related books, papers, videos, and toolboxes
Algorithms for outlier, adversarial and drift detection
Anomaly detection for streaming time series, featuring automated model selection.
NETS:Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing
Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping
[ICML 2024] Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
Outlier detection based on random forest models
Data and code for the experiments in the Outlier Detection task proposed by Camacho-Collados et al.
In the context of Deep Learning: What is the right way to conduct example weighting? How do you understand loss functions and so-called theorems on them?
Add noise to the color or coordinates of the point cloud.
Probabilistic outlier identification for bulk RNA sequencing data
A collection of free open-source tools to help you better understand your Outlier account, entirely handled in-browser.
State estimation for output with outlier (journal article matlab code) observer, Kalman-filter, Control
Visualize multidimensional outlier detection algorithms
This project uses statistical analysis to detect fraudulent credit card transactions by examining patterns and anomalies in a dataset of 10,000 transactions, calculating averages, medians, frequencies, and identifying outliers to distinguish between legitimate and fraudulent activities.