Cross-correlation Features

Cross-Correlation Features is a temporal feature engineering method that quantifies the similarity between two time series as a function of the displacement of one relative to the other, distinguishing itself by capturing lag-dependent linear relationships useful for predictive modeling.

198

Publications

9.1K

Citations

681

Authors

334

Institutions

Publications per year

2017–2026

84

Authors

681

  1. DD
    Debangshu Dey

    Jadavpur University, India

    4 publications · 123 citations

    4

    h-index

  2. SY
    Shihui Ying

    Shanghai University, China

    2 publications · 247 citations

    2

    h-index

  3. PR
    P. Rajamani

    Jadavpur University, India

    2 publications · 44 citations

    2

    h-index

  4. SO
    Scott Otterson

    University of Washington, United States

    2 publications · 67 citations

    2

    h-index

  5. SC
    S. Chakravorti

    Jadavpur University, India

    2 publications · 44 citations

    2

    h-index

1–5 of 681

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 144 citations

    6

    h-index

  2. Sensors

    5 publications · 153 citations

    5

    h-index

  3. The Astronomical Journal

    AJ · 4 publications · 197 citations

    4

    h-index

  4. 4

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 297 citations

    4

    h-index

1–5