ArticleStats2024
Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence.
Article in Stats, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Pseudotime-conditioned diffusion models for imputing time-series single-cell data.Bioinformatics advances · 2026Article
- Gene Regulatory Network Inference from Pseudotime-Ordered scRNA-seq Data via Time-Lagged Divergence Measures.Bioinformatics research and applications : ... international symposium, ISBRA ... proceedings. ISBRA (Conference) · 2025Article
- Reconstructing Dynamic Gene Regulatory Networks Using f-Divergence from Time-Series scRNA-Seq Data.Current issues in molecular biology · 2025Article
- Time-Varying Gene Regulatory Networks Inference Using KL Divergence from Single Cell Data.Proceedings of the ... International Conference on Bioinformatics and Biomedical Technology · 2025Article
- Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data.Stats · 2025Article
- Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence.Algorithms · 2025Article
- tBN-CSDI: a time-varying blue noise-based diffusion model for time-series imputation.Bioinformatics advances · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Change-point detection is a challenging problem that has a number of applications across various real-world domains. The primary objective of CPD is to identify specific time points where the underlying system undergoes transitions between different states, each characterized by its distinct data distribution. Precise identification of change points in time series omics data can provide insights into the dynamic and temporal characteristics inherent to complex biological systems. Many change-point detection methods have traditionally focused on the direct estimation of data distributions. However, these approaches become unrealistic in high-dimensional data analysis. Density ratio methods have emerged as promising approaches for change-point detection since estimating density ratios is easier than directly estimating individual densities. Nevertheless, the divergence measures used in these methods may suffer from numerical instability during computation. Additionally, the most popular
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.