outlier

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

Algorithms for outlier, adversarial and drift detection

Anomaly detection for streaming time series, featuring automated model selection.

Automagically remove trends from time-series data

A multi-agent framework to fully automate anomaly detection in different modalities, tabular, graph, time series, and more (work in progress)!

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

Outlier detection based on random forest models

Dimension reduction for outlier detection

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

Outliers handling in tidymodels

[NeurIPS 2026] Attention Sinks and Outliers in Attention Residuals

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

Detecting Outliers in Network Meta-Analysis

A collection of free open-source tools to help you better understand your Outlier account, entirely handled in-browser.