SOTAVerified

Change Point Detection

Change Point Detection is concerned with the accurate detection of abrupt and significant changes in the behavior of a time series.

Change point detection is the task of finding changes in the underlying model of a signal or time series. They are two main methods:

  1. Online methods, that aim to detect changes as soon as they occur in a real-time setting

  2. Offline methods that retrospectively detect changes when all samples are received.

Source: Selective review of offline change point detection methods

Papers

Showing 3140 of 285 papers

TitleStatusHype
Online Change Point Detection in Molecular Dynamics With Optical Random FeaturesCode1
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint DetectionCode1
Correlation-aware Unsupervised Change-point Detection via Graph Neural NetworksCode1
Fast and Attributed Change Detection on Dynamic Graphs with Density of StatesCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series MeasurementsCode0
An early warning system for emerging marketsCode0
Doubly Inhomogeneous Reinforcement LearningCode0
A fast topological approach for predicting anomalies in time-varying graphsCode0
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-DivergencesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LSTMCapsNAB (standard)27.77Unverified
2BinSeg CPD algorithm (Mahalanobis metric)NAB (standard)24.1Unverified
3OptEnsemble CPDE algorithm (WeightedSum+Rank)NAB (standard)23.07Unverified
4Opt CPD algorithm (Mahalanobis metric)NAB (standard)22.37Unverified
5WinEnsemble CPDE algorithm (Sum+MinAbs)NAB (standard)19.38Unverified
6Win CPD algorithm (l1 metric)NAB (standard)18.4Unverified
7BinSegEnsemble CPDE algorithm (WeightedSum+Rank)NAB (standard)18.1Unverified
#ModelMetricClaimedVerifiedStatus
1BinSegEnsemble CPDE algorithm (Min+MinMax/Rank)NAB (standard)41.81Unverified
2OptEnsemble CPDE algorithm (Min+MinMax/Rank)NAB (standard)41.81Unverified
3Opt CPD algorithm (Mahalanobis metric)NAB (standard)36.88Unverified
4BinSeg CPD algorithm (Mahalanobis metric)NAB (standard)36.88Unverified
5Win CPD algorithm (Mahalanobis metric)NAB (standard)27.79Unverified
6WinEnsemble CPDE algorithm (WeightedSum+MinAbs)NAB (standard)25.14Unverified
#ModelMetricClaimedVerifiedStatus
1Parameter-free ClaSPCovering0.85Unverified
2ESPRESSOCovering0.44Unverified
3BOCDRelative Change Point Distance0.2Unverified
4ClaSPRelative Change Point Distance0.01Unverified