Event-based Features

Event-Based Features is a class of time series features derived from the temporal, structural, or statistical characteristics of discrete events, distinguished by their focus on capturing patterns associated with specific occurrences or transitions within a sequence rather than on continuous signal properties.

92

Publications

6.7K

Citations

316

Authors

157

Institutions

Publications per year

2017–2026

45

Authors

316

  1. SK
    Sara Klingenstein

    University of Colorado Boulder, United States

    3 publications · 65 citations

    3

    h-index

  2. JM
    James Martin

    University of Colorado Boulder, United States

    3 publications · 65 citations

    3

    h-index

  3. SB
    Steven Bethard

    University of Arizona, United States

    3 publications · 65 citations

    3

    h-index

  4. CN
    Christopher N. Wahlheim

    Washington University in St. Louis, United States

    3 publications · 111 citations

    3

    h-index

  5. JM
    Jeffrey M. Zacks

    Washington University in St. Louis, United States

    3 publications · 111 citations

    3

    h-index

1–5 of 316

Venues

  1. Journal of Neuroscience

    3 publications · 280 citations

    3

    h-index

  2. Child Development

    3 publications · 296 citations

    3

    h-index

  3. IEEE Access

    3 publications · 90 citations

    3

    h-index

  4. 2

    h-index

  5. International Conference on Semantic Computing (ICSC 2007)

    Conference · 2 publications · 42 citations

    2

    h-index

1–5