Random Walk Features

Random Walk Features is a graph feature engineering method that generates node or graph representations by extracting statistical patterns from sequences of vertices traversed through stochastic walks, distinguishing it from other feature extraction techniques by its reliance on the topological dynamics of probabilistic paths.

37

Publications

1.4K

Citations

102

Authors

67

Institutions

Publications per year

2017–2026

12

Authors

102

  1. JS
    John Steele

    Durham University, United Kingdom

    2 publications · 42 citations

    2

    h-index

  2. GP
    Girijesh Prasad

    University of Ulster, United Kingdom

    2 publications · 35 citations

    2

    h-index

  3. BO
    Brian Odegaard

    University of California, Los Angeles, United States

    2 publications · 65 citations

    2

    h-index

  4. JW
    Joseph W. Goodman

    Stanford University, United States

    2 publications · 33 citations

    2

    h-index

  5. PY
    Pratheepan Yogarajah

    University of Ulster, United Kingdom

    2 publications · 35 citations

    2

    h-index

1–5 of 102

Venues

  1. Proceedings of the American Mathematical Society

    PROC · 2 publications · 42 citations

    2

    h-index

  2. Physical Review A

    PRA · 2 publications · 225 citations

    2

    h-index

  3. BMC Bioinformatics

    1 publications · 47 citations

    1

    h-index

  4. Physical Review E

    PRE · 1 publications · 54 citations

    1

    h-index

  5. Ulster University Research Portal (Ulster University)

    Repository · 1 publications · 15 citations

    1

    h-index

1–5