Repulsive Point Processes

Repulsive Point Processes is a class of stochastic point process models in spatial statistics that generate patterns characterized by inhibition or dispersion, where the occurrence of a point reduces the likelihood of nearby points, thereby distinguishing it from random or clustered processes.

57

Publications

3.2K

Citations

118

Authors

86

Institutions

Publications per year

2017–2026

21

Authors

118

  1. FL
    Frédéric Lavancier

    Laboratoire de Mathématiques Jean Leray, France

    4 publications · 321 citations

    4

    h-index

  2. BT
    Ben Taskar

    University of Pennsylvania, United States

    4 publications · 269 citations

    4

    h-index

  3. RB
    Rémi Bardenet

    Centre National de la Recherche Scientifique, France

    3 publications · 87 citations

    3

    h-index

  4. JM
    Jesper Møller

    Aalborg University, Denmark

    3 publications · 287 citations

    3

    h-index

  5. AK
    Alex Kulesza

    University of Pennsylvania, United States

    3 publications · 836 citations

    3

    h-index

1–5 of 118

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 106 citations

    6

    h-index

  2. Advances in Applied Probability

    AAP · 5 publications · 722 citations

    5

    h-index

  3. IEEE Transactions on Communications

    3 publications · 143 citations

    3

    h-index

  4. Bernoulli

    2 publications · 95 citations

    2

    h-index

  5. Neural Information Processing Systems

    Conference · 2 publications · 54 citations

    2

    h-index

1–5