Time Series Clustering

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Overview

Time series clustering aims to find groups of sequences with similar shapes, behaviors, or temporal regimes, supporting tasks such as customer segmentation, patient profiling, and anomaly analysis. Approaches range from elastic distances such as dynamic time warping and Move-Split-Merge to feature-based methods, neural representations, graph clustering, and models that explicitly capture changing states. Researchers evaluate methods on standard time-series benchmarks and domain data, while addressing variable lengths, noise, missing values, distribution shifts, and the cost of large datasets. A central tension is how to balance flexible alignment and strong clustering performance with interpretable groups, reliable choices of cluster structure, and robustness across applications.

Latest papers

CardsList

28 papers5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. The Clustering Occupation Kernel (CLOCK) Method for Time Series Arising from Dynamical Systems

    Oct 23, 2026Michael L. Wells, Kamel Lahouel, Victor Rielly +1Time Series ClusteringKernel Methods

    Fariborz Maseeh Department of Mathematics and Statistics, Portland State University, Portland, OR 97201 · Translational Genomics Research Institute, Phoenix, AZ 85004

  2. Coincidence-Maximizing Customer Clustering Using Smart Meter Data

    Oct 20, 2026Ramiro H. Gálvez, Gabriel Martos Venturini, Iván MondrzakClusteringPower Systems

    Universidad Torcuato Di Tella, Ciudad de Buenos Aires, Argentina.

  3. Longitudinal Learner Participation Profiling in Online Learning: Heterogeneous Consensus Clustering under Unequal Observation Windows

    Oct 12, 2026David Otoo-Arthur, Terence L. van ZylEducational Data MiningClustering

    University of the Witwatersrand, Johannesburg, South Africa · University of Johannesburg, Johannesburg, South Africa

  4. Seeing Time: Visual-Temporal Representation Learning for Interpretable Time Series Clustering

    Sep 29, 2026Zheng Zhu, Zexi Tan, Yuming Deng +1Time Series ClusteringTime Series Representation Learning

    Huizhou No. 1 High School (High School Student) · Guangdong University of Technology · South China University of Technology

  5. Functional Autoencoders for Amplitude-Phase Representation Learning

    Sep 28, 2026Peida Wu, Xinyang Xiong, Pengcheng ZengFunctional Data AnalysisRepresentation Learning

    School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA · Institute of Mathematical Sciences, ShanghaiTech University, Shanghai, China

  6. CLUES-WEASEL: No additional clues required to choose your time series clustering algorithm

    Sep 7, 2026Johann FaouziClusteringUnsupervised Clustering

    Univ Rennes, Ensai, CNRS, CREST - UMR 9194, F-35000 Rennes, France.

  7. QSMP: finding representative time series subsequences through Quick Shift+Matrix Profile

    Aug 16, 2026Carlos H. Mendoza-Cardenas, Rogers F. Silva, Austin J. BrockmeierTime Series Clustering

    Twitch Interactive, San Francisco, California, USA · Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA · TReNDS Center, Atlanta, GA, USA +1

  8. Connected Subspace Clustering: Hardness, a Scalable Heuristic, and an Application to Sea Level Geodesy

    Aug 14, 2026Johanna Hillebrand, Jan Höckendorff, Jürgen Kusche +5ClusteringTime Series Clustering

    Heinrich Heine University Düsseldorf, Universitätsstraße 1, 40225 Düsseldorf, Germany · University of Cologne, Albertus-Magnus-Platz, 50923 Köln, Germany · University of Bonn, Regina-Pacis-Weg 3, 53115 Bonn, Germany +1

  9. STCAD: Scalable Trajectory Clustering and Anomaly Detection on Terabyte-Scale AIS Data

    Aug 10, 2026Bertram Hage, Alexander Schiøtz, Felix Thomsen +2Unsupervised Anomaly DetectionTime Series Clustering

    Technical University of Denmark Anker Engelunds Vej 101 2800 Kongens Lyngby, Denmark

  10. MINT: Tensor Decomposition on Stacked Recurrence Matrices for Time Series Data Mining

    Aug 4, 2026Kaamil Kaka, Audrey Der, Evangelos E. Papalexakis +2ClusteringTime Series Clustering

    University of California, Riverside, Department of Computer Science · Neuralix AI

  11. Wiring diagram extraction and gluing: a case study in classifying figure skating jumps using 3D dataset

    Jul 30, 2026Jason Lo, Mohammadnima JafariTime Series Clustering

  12. Contrastive Representation Learning of Longitudinal Disease Trajectories on Temporal Graphs

    Jul 28, 2026Bastian PfeiferTemporal GNNsDisease Progression Modeling

    Institute for Medical Informatics, Statistics and Documentation · Medical University Graz · Graz, Austria

  13. CASC: Causal Adversarial Subspace Clustering for Multivariate Spatiotemporal Data

    Jul 23, 2026Francis Ndikum Nji, Vandana Janeja, Jianwu WangCausal Representation LearningClustering

    Dept. of Information Systems University of Maryland, Baltimore County Baltimore, MD, U.S.A

  14. Clustering algorithms for multivariate wind farm SCADA data filtering

    Jul 15, 2026Nicolò Italiano, Vasilis Pettas, Tuhfe Göçmen +1Unsupervised ClusteringUnsupervised Anomaly Detection

    Department of Wind and Energy Systems, Technical University of Denmark, Frederiksborgvej 399, Roskilde, 4000, Denmark

  15. Terminal Dimension Reduction for Time Series with Applications

    Jul 10, 2026Alexander Munteanu, Matteo Russo, David Saulpic +1Coreset SelectionDimensionality Reduction

    TU Dortmund, Germany · EPFL, Switzerland · CNRS & Université Paris Cité, IRIF, Paris, France +1

  16. FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series

    Jul 8, 2026Donato Cerciello, Leonardo Schiavo, Angel Panizo-LLedot +2Self-Supervised Time Series Representation LearningClustering

    Departamento de Sistemas Inform´aticos, Universidad Polit´ecnica de Madrid Madrid, Spain

  17. NEST: Tackling Dataset-Level Distribution Shifts via Regime-Oriented Mixture-of-Experts

    Jul 7, 2026Lanhao Li, Bingshu Xie, Lijun Sun +3Multivariate Time Series ForecastingLong-Term Time Series Forecasting

    1Beihang University

  18. Robust State-Conditional Feature-Weighted Jump Models for Temporal Clustering

    Jun 11, 2026Federico P. Cortese, Alessio FarcomeniClusteringUnsupervised Clustering

    University of Milan, Department of Economics, Management, and Quantitative Methods · National Research Council of Italy, Institute for Applied Mathematics and Information Technologies, Milan · University of Rome “Tor Vergata”, Department of Enterprise Engineering

  19. Efficient Time Series Clustering from Multiscale Reservoir Dynamics with Granular-Ball Anchoring Graph Optimization

    Jun 10, 2026Yifan Wang, Lifeng Shen, Shuyin Xia +1ClusteringTime Series Clustering

    Chongqing Key Laboratory of Computational Intelligence, Key Laboratory of Cyberspace Big Data Intelligent Security, Ministry of Education, Sichuan-Chongqing Co-construction Key Laboratory of Digital Economy Intelligence and Key Laboratory of Big Data Intelligent Computing, College of Computer Science and Technology, Chongqing University of Posts and Telecommunications · Chongqing Ant Consumer Finance Co,. Ltd, Ant Group.

  20. An Analytical Multiple Criteria Framework for Temporal and Dynamic Business-to-Business Customer Segmentation in Manufacturing

    May 16, 2026Muhammad Raees, Konstantinos Papangelis, Vassilis Javed KhanClusteringMulti-Criteria Decision Analysis

    Rochester Institute of Technology Rochester NY USA · Independent Researcher

  21. Amortized Neural Clustering of Time Series based on Statistical Features

    May 13, 2026Ángel López-Oriona, Ying SunCluster Number EstimationAmortized Inference

    CEMSE Division, Statistics Program, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia. · Statistics Program, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

  22. Scalable inference of spatial regions and temporal signatures from time series

    May 6, 2026Jiayu Weng, Alec KirkleyClusteringTime Series Clustering

    Institute of Data Science, University of Hong Kong, Hong Kong SAR, China · School of Computing and Data Science, University of Hong Kong, Hong Kong SAR, China · Department of Urban Planning and Design, University of Hong Kong, Hong Kong SAR, China +1

  23. Soft-MSM: Differentiable Context-Aware Elastic Alignment for Time Series

    Apr 30, 2026Christopher Holder, Anthony BagnallDynamic Time WarpingTime Series Classification

    School of Electronics and Computer Science University of Southampton Southampton, SO17 1BJ, United Kingdom

  24. Deep Clustering for Climate: Analyzing Teleconnections through Learned Categorical States

    Apr 24, 2026Lívia Meinhardt, Dário OliveiraRepresentation LearningTime Series Classification

    FGV EMAp

  25. GALACTIC: Global and Local Agnostic Counterfactuals for Time-series Clustering

    Mar 5, 2026Christos Fragkathoulas, Eleni Psaroudaki, Themis Palpanas +1Counterfactual ExplanationsTime Series Clustering

    University of Ioannina Ioannina, Greece · Archimedes, Athena Research Center Athens, Greece · Université Paris Cité, LIPADE, F-75006 Paris, France

  26. Introducing Feature-Based Trajectory Clustering, a clustering algorithm for longitudinal data

    Feb 24, 2026Marie-Pierre Sylvestre, Laurence BoulangerTime Series Clustering

  27. CROCS: A Two-Stage Clustering Framework for Behaviour-Centric Consumer Segmentation with Smart Meter Data

    Jan 15, 2026Luke W. Yerbury, Ricardo J. G. B. Campello, G. C. Livingston +2ClusteringDemand Response

  28. Bayesian Nonparametric Dynamical Clustering of Time Series

    Oct 8, 2025Adrián Pérez-Herrero, Paulo Félix, Jesús Presedo +1Time Series ClusteringRegime-Switching Dynamical Systems

    CiTIUS (Centro Singular de Investigación en Tecnoloxías Intelixentes), Universidade de Santiago de Compostela, Santiago de Compostela, 15782 Spain. · Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Avenue, Cambridge, CB3 0FD, United Kingdom.