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Change point detection for clustered expression data [PDF]
BMC Genomics, 2022 Background To detect changes in biological processes, samples are often studied at several time points. We examined expression data measured at different developmental stages, or more broadly, historical data.
Miriam Sieg +3 more
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Change-Point Detection for Multi-Way Tensor-Based Frameworks [PDF]
Entropy, 2023 Graph-based change-point detection methods are often applied due to their advantages for using high-dimensional data. Most applications focus on extracting effective information of objects while ignoring their main features. However, in some applications,
Shanshan Qin, Ge Zhou, Yuehua Wu
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Noise-Adaptive State Estimators with Change-Point Detection [PDF]
SensorsAiming at tracking sharply maneuvering targets, this paper develops novel variational adaptive state estimators for joint target state and process noise parameter estimation for a class of linear state-space models with abruptly changing parameters.
Xiaolei Hou +3 more
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Leveraging change point detection to discover natural experiments in data [PDF]
EPJ Data Science, 2022 Change point detection has many practical applications, from anomaly detection in data to scene changes in robotics; however, finding changes in high dimensional data is an ongoing challenge. We describe a self-training model-agnostic framework to detect
Yuzi He +2 more
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Size agnostic change point detection framework for evolving networks. [PDF]
PLoS ONE, 2020 Changes in the structure of observed social and complex networks can indicate a significant underlying change in an organization, or reflect the response of the network to an external event.
Hadar Miller, Osnat Mokryn
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Sequential Change-Point Detection via Online Convex Optimization [PDF]
Entropy, 2018 Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential ...
Yang Cao, Liyan Xie, Yao Xie, Huan Xu
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3D Change Detection Using Adaptive Thresholds Based on Local Point Cloud Density
ISPRS International Journal of Geo-Information, 2021 In recent years, because of highly developed LiDAR (Light Detection and Ranging) technologies, there has been increasing demand for 3D change detection in urban monitoring, urban model updating, and disaster assessment.
Dan Liu +3 more
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Change-Point Detection Using the Conditional Entropy of Ordinal Patterns [PDF]
Entropy, 2018 This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated.
Anton M. Unakafov, Karsten Keller
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A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals [PDF]
Frontiers in Physiology, 2018 Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change ...
Nathan Gold +4 more
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3D CHANGE DETECTION OF POINT CLOUDS BASED ON DENSITY ADAPTIVE LOCAL EUCLIDEAN DISTANCE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 With the development of sensors and multi-view stereo matching technology, image-based dense matching point cloud data shares higher geometric accuracy and richer spectral information, and such data is therefore widely used in change detection-related ...
J. X. Chai, Y. S. Zhang, Z. Yang, J. Wu
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