Twitter's Anomaly Detection in Pure Python

Easier CUSUM control charts. Returns simple CUSUM statistics, CUSUMs with control limit calculations, and function to generate faceted CUSUM Control Charts

Different flavours of CUSUM for change point detection.

IMU fault detection

Fast Online Changepoint Detection via Functional Pruning CUSUM statistics

Quickest Change Detection for Unnormalized Statistical Models

Social Networks Monitoring

Statistical volume anomaly detection for trade streams - Hawkes process, CUSUM, and Bayesian Online Changepoint Detection (BOCPD). Zero dependencies. TypeScript.

Anomaly Detection in Sensor Data (LIT101) from Secure Water Treatment (SWaT) testbed . Demo of CUSUM and MLP methodologies.

NASA Bearing Dataset: Fault Detection with Wiener denoising and custom time-frequency btstft Transforms

CUSUM is the cumulative sum of the samples and CUMEAN is the cumulative sum of the updated samples with their mean. CUSUM and CUMEAN can detect relatively small changes in a process mean. They can be more useful in the time series dataset.

This repository represents additional control charts, various plans and variables that are used within the chart scope using Minitab software

NCIs Project 2024/25

Streaming anomaly detection in Rust — detectors, calibration, SOC triage. Powers eBPFsentinel

Changepoint detection toolkit for offline and online in Rust with Python bindings

A Python library to address the Change Detection problem using the CUSUM and CPM methods, implemented with NumPy and SciPy. The CPM implementation closely matches the R version, providing a solid alternative for Python users.

A hardware–software co-design of the CUSUM streaming anomaly detector. Includes hardware modules, a software reference implementation, and Python tools for validating correctness and profiling performance across platforms.

Regime detection without religion — six algorithms (HMM, BOCPD, CUSUM, GMM, BinSeg, Ensemble), one harness, reproducible leaderboard.

Synthetic EHM analytics project — ISA corrections, GPA degradation modelling, CUSUM anomaly detection, and XGBoost/LSTM RUL prediction for a 20-engine turbofan fleet.