Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
Not on the map. Why?
Abstract (arXiv)
Bayesian On-line Changepoint Detection is extended to on-line model selection and non-stationary spatio-temporal processes. We propose spatially structured Vector Autoregressions (VARs) for modelling the process between changepoints (CPs) and give an upper bound on the approximation error of such models. The resulting algorithm performs prediction, model selection and CP detection on-line. Its time complexity is linear and its space complexity constant, and thus it is two orders of magnitudes faster than its closest competitor. In addition, it outperforms the state of the art for multivariate data.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 May 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 4; 2023: 4; 2024: 2; 2025: 0; 2026: 2.
13 papers.
Sort:
- 2023Robust and Scalable Bayesian Online Changepoint Detectioncited by 16
- 2022WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Datacited by 13
- 2022Memory-free Online Change-point Detection: A Novel Neural Network Approachcited by 5
- 2024A unifying framework for generalised Bayesian online learning in non-stationary environmentscited by 5
- 2023Creation and evaluation of timelines for longitudinal user postscited by 4
- 2022Latent Neural Stochastic Differential Equations for Change Point Detectioncited by 2
- 2023Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processescited by 2
- 2021EVARS-GPR: EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Datacited by 1
- 2022Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detectioncited by 0
- 2023Greedy online change point detectioncited by 0
- 2024RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detectioncited by 0
- 2026Stream Assembly Is an Uncontrolled Treatment in Streaming Intrusion-Detection Benchmarkscited by 0
- 2026High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability21 Sep 2026
- 2026Stream Assembly Is an Uncontrolled Treatment in Streaming Intrusion-Detection Benchmarks23 May 2026
- 2024A unifying framework for generalised Bayesian online learning in non-stationary environments15 Nov 2024
- 2024RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection12 Jul 2024
- 2023Greedy online change point detection14 Aug 2023
- 2023Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes1 Apr 2023
- 2023Creation and evaluation of timelines for longitudinal user posts10 Mar 2023
- 2023Robust and Scalable Bayesian Online Changepoint Detection9 Feb 2023
- 2022Latent Neural Stochastic Differential Equations for Change Point Detection22 Aug 2022
- 2022Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection9 Aug 2022
- 2022Memory-free Online Change-point Detection: A Novel Neural Network Approach8 Jul 2022
- 2022WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data18 Jan 2022
- 2023Robust and Scalable Bayesian Online Changepoint Detectioncited by 16
- 2022WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Datacited by 13
- 2022Memory-free Online Change-point Detection: A Novel Neural Network Approachcited by 5
- 2024A unifying framework for generalised Bayesian online learning in non-stationary environmentscited by 5
- 2023Creation and evaluation of timelines for longitudinal user postscited by 4
- 2022Latent Neural Stochastic Differential Equations for Change Point Detectioncited by 2
- 2023Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processescited by 2
- 2021EVARS-GPR: EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal Datacited by 1
- 2022Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detectioncited by 0
- 2023Greedy online change point detectioncited by 0
- 2024RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detectioncited by 0
- 2026Stream Assembly Is an Uncontrolled Treatment in Streaming Intrusion-Detection Benchmarkscited by 0
12 most cited of 13 All 13 (JSON)
- 2026High-Dimensional Online Change Point Detection with Adaptive Thresholding and Interpretability21 Sep 2026
- 2026Stream Assembly Is an Uncontrolled Treatment in Streaming Intrusion-Detection Benchmarks23 May 2026
- 2024A unifying framework for generalised Bayesian online learning in non-stationary environments15 Nov 2024
- 2024RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection12 Jul 2024
- 2023Greedy online change point detection14 Aug 2023
- 2023Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes1 Apr 2023
- 2023Creation and evaluation of timelines for longitudinal user posts10 Mar 2023
- 2023Robust and Scalable Bayesian Online Changepoint Detection9 Feb 2023
- 2022Latent Neural Stochastic Differential Equations for Change Point Detection22 Aug 2022
- 2022Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection9 Aug 2022
- 2022Memory-free Online Change-point Detection: A Novel Neural Network Approach8 Jul 2022
- 2022WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data18 Jan 2022
12 newest of 13 All 13 (JSON)