Papers Clustering Multivariate Time Series

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CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering

2025-05-20 · Isabella Degen, Zahraa S Abdallah, Henry W J Reeve, Kate Robson Brown

Time series clustering promises to uncover hidden structural patterns in data with applications across healthcare, finance, industrial systems, and other critical domains. However, without validated ground truth informat…

Clustering Clustering Algorithms Evaluation Clustering Multivariate Time Series Time Series+1

FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis

2025-05-12 · Ziling Ma, Ángel López-Oriona, Hernando Ombao, Ying Sun

Clustering multivariate time series data is a crucial task in many domains, as it enables the identification of meaningful patterns and groups in time-evolving data. Traditional approaches, such as crisp clustering, rely…

Clustering Clustering Multivariate Time Series Time Series

Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering

2024-01-15 · Hamid Ghaderi, Brandon Foreman, Chandan K. Reddy, Vignesh Subbian

Traumatic Brain Injury (TBI) presents a broad spectrum of clinical presentations and outcomes due to its inherent heterogeneity, leading to diverse recovery trajectories and varied therapeutic responses. While many studi…

Clustering Clustering Multivariate Time Series Missing Values Self-Supervised Learning+2

A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping

2023-02-27 · Hamid Ghaderi, Brandon Foreman, Amin Nayebi, Sindhu Tipirneni 외

Self-supervised learning approaches provide a promising direction for clustering multivariate time-series data. However, real-world time-series data often include missing values, and the existing approaches require imput…

Clinical Knowledge Clustering Clustering Multivariate Time Series Missing Values+4

Clustering individuals based on multivariate EMA time-series data

2022-12-02 · Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp, Anne Roefs

In the field of psychopathology, Ecological Momentary Assessment (EMA) methodological advancements have offered new opportunities to collect time-intensive, repeated and intra-individual measurements. This way, a large a…

Clustering Clustering Multivariate Time Series Time Series Time Series Analysis

Autoencoder Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm

2022-09-09 · Jonas Köhne, Lars Henning, Clemens Gühmann

This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become more …

Clustering Clustering Algorithms Evaluation Clustering Multivariate Time Series Time Series+1

Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques

2021-09-22 · Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar, Borja Lafuente-Rego

Three robust methods for clustering multivariate time series from the point of view of generating processes are proposed. The procedures are robust versions of a fuzzy C-means model based on: (i) estimates of the quantil…

Clustering Clustering Multivariate Time Series Time Series Time Series Analysis

Dynamic clustering of time series data

2020-01-28 · Victhor S. Sartório, Thaís C. O. Fonseca

We propose a new method for clustering multivariate time-series data based on Dynamic Linear Models. Whereas usual time-series clustering methods obtain static membership parameters, our proposal allows each time-series …

Clustering Clustering Multivariate Time Series Time Series Time Series Analysis+1

ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs

2019-02-27 · Amir Gholami, Kurt Keutzer, George Biros

Residual neural networks can be viewed as the forward Euler discretization of an Ordinary Differential Equation (ODE) with a unit time step. This has recently motivated researchers to explore other discretization approac…

Clustering Multivariate Time Series Multivariate Time Series Imputation

Optimal Transport vs. Fisher-Rao distance between Copulas for Clustering Multivariate Time Series

2016-04-28 · Gautier Marti, Sébastien Andler, Frank Nielsen, Philippe Donnat

We present a methodology for clustering N objects which are described by multivariate time series, i.e. several sequences of real-valued random variables. This clustering methodology leverages copulas which are distribut…

Clustering Clustering Multivariate Time Series Time Series Time Series Analysis

Optimal Copula Transport for Clustering Multivariate Time Series

2015-09-27 · Gautier Marti, Frank Nielsen, Philippe Donnat

This paper presents a new methodology for clustering multivariate time series leveraging optimal transport between copulas. Copulas are used to encode both (i) intra-dependence of a multivariate time series, and (ii) int…

Clustering Clustering Multivariate Time Series Time Series Time Series Analysis