Multivariate Time Series Classification

Multivariate Time Series Classification is a time series classification task that involves assigning class labels to temporal sequences composed of multiple interrelated variables observed over time, distinguishing it from univariate variants by exploiting the joint dynamics across multiple channels.

308

Publications

20K

Citations

1K

Authors

411

Institutions

Publications per year

2017–2026

204

Authors

1K

  1. GH
    Guoliang He

    Wuhan University, China

    8 publications · 244 citations

    8

    h-index

  2. YS
    Yuval Shaḥar

    Ben-Gurion University of the Negev, Israel

    4 publications · 367 citations

    4

    h-index

  3. MG
    Mohamed Ghalwash

    Ain Shams University, Egypt

    4 publications · 215 citations

    4

    h-index

  4. AB
    Anthony Bagnall

    University of East Anglia, United Kingdom

    4 publications · 246 citations

    4

    h-index

  5. ZO
    Zoran Obradović

    Temple University, United States

    4 publications · 215 citations

    4

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 20 publications · 1.6K citations

    15

    h-index

  2. Expert Systems with Applications

    11 publications · 545 citations

    11

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 8 publications · 1.3K citations

    8

    h-index

  4. Data Mining and Knowledge Discovery

    7 publications · 758 citations

    7

    h-index

  5. Knowledge-Based Systems

    6 publications · 327 citations

    6

    h-index

1–5