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.

Automagically remove trends from time-series data

RANSAC Template Library

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

Data and code for the experiments in the Outlier Detection task proposed by Camacho-Collados et al.

Dimension reduction for outlier detection

Outlier detection based on random forest models

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.

Outliers handling in tidymodels

Probabilistic outlier identification for bulk RNA sequencing data

Detecting Outliers in Network Meta-Analysis

State estimation for output with outlier (journal article matlab code) observer, Kalman-filter, Control

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

Implementation of Hampel filter in Python, including multiprocessor support, and interactive plotting with plotly and IPywidgets.

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.