26.1.5.1 Multivariant Time Series Analysis

Chapter Contents (Back)
Time Series. Multi-Variable. Multivariant. Multiple variables.

Yang, C., Le Bouquin Jeannes, R., Faucon, G., Shu, H.,
Extracting Information on Flow Direction in Multivariate Time Series,
SPLetters(18), No. 4, April 2011, pp. 251-254.
IEEE DOI 1103
BibRef

Diversi, R.[Roberto], Guidorzi, R.[Roberto],
Optimal filtering of multivariate noisy AR processes,
SIViP(7), No. 5, September 2013, pp. 873-878.
Springer DOI 1309
BibRef

Tuncel, K.S.[Kerem Sinan], Baydogan, M.G.[Mustafa Gokce],
Autoregressive forests for multivariate time series modeling,
PR(73), No. 1, 2018, pp. 202-215.
Elsevier DOI 1709
Multivariate time series BibRef

Mikalsen, K.Ø.[Karl Øyvind], Bianchi, F.M.[Filippo Maria], Soguero-Ruiz, C.[Cristina], Jenssen, R.[Robert],
Time series cluster kernel for learning similarities between multivariate time series with missing data,
PR(76), No. 1, 2018, pp. 569-581.
Elsevier DOI 1801
Multivariate time series BibRef

Bianchi, F.M.[Filippo Maria], Livi, L.[Lorenzo], Mikalsen, K.Ø.[Karl Øyvind], Kampffmeyer, M.[Michael], Jenssen, R.[Robert],
Learning representations of multivariate time series with missing data,
PR(96), 2019, pp. 106973.
Elsevier DOI 1909
Representation learning, Multivariate time series, Autoencoders, Recurrent neural networks, Kernel methods BibRef

ur Rehman, N.[Naveed], Khan, B.[Bushra], Naveed, K.[Khuram],
Data-Driven Multivariate Signal Denoising Using Mahalanobis Distance,
SPLetters(26), No. 9, September 2019, pp. 1408-1412.
IEEE DOI 1909
Noise reduction, Covariance matrices, Correlation, Signal processing algorithms, Gaussian noise, multivariate empirical mode decomposition BibRef

Lim, H.K.[Hyun-Ki], Choi, H.[Heeseung], Choi, Y.[Yeji], Kim, I.J.[Ig-Jae],
Memetic algorithm for multivariate time-series segmentation,
PRL(138), 2020, pp. 60-67.
Elsevier DOI 2010
Time series segmentation, Multivariate data, Memetic algorithm BibRef

Li, Q.Z.[Qing-Zhe], Zhao, L.[Liang], Lee, Y.C.[Yi-Ching], Sassan, A.[Avesta], Lin, J.[Jessica],
CPM: A general feature dependency pattern mining framework for contrast multivariate time series,
PR(112), 2021, pp. 107711.
Elsevier DOI 2102
Contrast pattern, Feature dependency, Controlled experiment, Driving behavior, Multivariate time series BibRef

Li, H.L.[Hai-Lin], Liu, Z.C.[Ze-Chen],
Multivariate time series clustering based on complex network,
PR(115), 2021, pp. 107919.
Elsevier DOI 2104
Multivariate time series, Data mining, Clustering analysis, Complex network BibRef

Yildiz, A.Y.[A. Yarkin], Koç, E.[Emirhan], Koç, A.[Aykut],
Multivariate Time Series Imputation With Transformers,
SPLetters(29), 2022, pp. 2517-2521.
IEEE DOI 2301
Transformers, Time series analysis, Training, Decoding, Data models, Medical services, Computational modeling, Deep learning, unsupervised learning BibRef

Roques, A.[Axel], Zhao, A.[Anne],
Association Rules Discovery of Deviant Events in Multivariate Time Series: An Analysis and Implementation of the SAX-ARM Algorithm,
IPOL(12), 2022, pp. 604-624.
DOI Link 2301
Code, Time Series. Tims Series analysis. BibRef

Zhang, N.[Nan], Sun, S.L.[Shi-Liang],
Multiview Unsupervised Shapelet Learning for Multivariate Time Series Clustering,
PAMI(45), No. 4, April 2023, pp. 4981-4996.
IEEE DOI 2303
Time series analysis, Adaptation models, Task analysis, Learning systems, Sun, Representation learning, Correlation, adaptive neighbor BibRef

Younis, R.[Raneen], Hakmeh, A.[Abdul], Ahmadi, Z.[Zahra],
MTS2Graph: Interpretable multivariate time series classification with temporal evolving graphs,
PR(152), 2024, pp. 110486.
Elsevier DOI Code:
WWW Link. 2405
Multivariate time series, Interpretability, Neural networks, Classification BibRef

Gu, Y.L.[Yong-Li], Yan, X.[Xiang], Qin, H.L.[Han-Lin], Akhtar, N.[Naveed], Yuan, S.[Shuai], Fu, H.H.[Hong-Hao], Yang, S.[Shuowen], Mian, A.[Ajmal],
HDTCNet: A hybrid-dimensional convolutional network for multivariate time series classification,
PR(168), 2025, pp. 111837.
Elsevier DOI Code:
WWW Link. 2506
Multivariate time series, Classification, Wavelet transform, Difference calculation, Convolutional network BibRef

Gui, H.Y.[Hao-Yu], Tang, X.H.[Xiang-Hong], Li, G.J.[Guan-Jun], Wang, C.B.[Chao-Bin], Lu, J.G.[Jian-Guang],
A novel dynamic graph attention aggregation network for multivariate time series classification,
PR(172), 2026, pp. 112732.
Elsevier DOI 2601
Multivariate time series classification, Graph attention convolutional network, Temporal dynamic relationships BibRef

Rozin, B.[Bionda], Pedronette, D.C.G.[Daniel C.G.],
A ranked-based framework based on manifold learning for multivariate time series retrieval and classification,
PRL(202), 2026, pp. 36-43.
Elsevier DOI 2603
Multivariate time series, Representation, Information retrieval, Classification, Manifold learning BibRef

Di, Y.[Yi], Wang, F.[Fujin], Zhai, Z.[Zhi], Zhao, Z.B.[Zhi-Bin], Chen, X.F.[Xue-Feng],
Beyond the homophily assumption: Mining complex correlations in time series via graph neural network,
PR(178), 2026, pp. 113388.
Elsevier DOI Code:
WWW Link. 2605
Multivariate time series, Graph neural network, Complex multi-sensor system, Spatial information, Nonlinear correlation BibRef

Silva, M.G.[Miguel G.], Madeira, S.C.[Sara C.], Henriques, R.[Rui],
On why and how statistical significance criteria can guide multivariate time series motif analysis,
PRL(205), 2026, pp. 66-72.
Elsevier DOI 2605
Motif discovery, Statistical significance, Multivariate time series, Temporal pattern mining BibRef


Garg, Y.[Yash], Candan, K.S.[K. Selçuk],
SDMA: Saliency-Driven Mutual Cross Attention for Multi-Variate Time Series,
ICPR21(7242-7249)
IEEE DOI 2105
Time series analysis, Gesture recognition, Data models, Multiaccess communication, Noise measurement, Optimization BibRef

Reittu, H.[Hannu], Bazsó, F.[Fülöp], Weiss, R.[Robert],
Regular Decomposition of Multivariate Time Series and Other Matrices,
SSSPR14(424-433).
Springer DOI 1408
BibRef

Liu, R.Q.[Ruo-Qian], Xu, S.[Shen], Fang, C.[Chen], Liu, Y.W.[Yung-Wen], Murphey, Y.L.[Yi L.], Kochhar, D.S.[Dev S.],
Statistical modeling and signal selection in multivariate time series pattern classification,
ICPR12(2853-2856).
WWW Link. 1302
BibRef

Chandrakala, S., Sekhar, C.C.[C. Chandra],
Classification of Multi-variate Varying Length Time Series Using Descriptive Statistical Features,
PReMI09(13-18).
Springer DOI 0912
BibRef

Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Time Series Anomaly Detection .


Last update:Sep 21, 2026 at 18:29:27