Probabilistic Logic Programming

Probabilistic Logic Programming is a formal framework within logic programming that extends deterministic logic programs by incorporating probabilistic semantics to represent and reason about uncertain knowledge using distributions over possible worlds.

95

Publications

4.4K

Citations

158

Authors

84

Institutions

Publications per year

2017–2026

18

Authors

158

  1. FR
    Fabrizio Riguzzi

    University of Ferrara, Italy

    19 publications · 524 citations

    15

    h-index

  2. LD
    Luc De Raedt

    KU Leuven, Belgium

    17 publications · 1.2K citations

    13

    h-index

  3. EB
    Elena Bellodi

    University of Ferrara, Italy

    12 publications · 343 citations

    11

    h-index

  4. GV
    Guy Van den Broeck

    KU Leuven, Belgium

    9 publications · 570 citations

    9

    h-index

  5. RZ
    Riccardo Zese

    University of Ferrara, Italy

    8 publications · 242 citations

    8

    h-index

1–5 of 158

Venues

  1. Theory and Practice of Logic Programming

    13 publications · 738 citations

    12

    h-index

  2. arXiv (Cornell University)

    Repository · 6 publications · 419 citations

    6

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 189 citations

    6

    h-index

  4. Machine Learning

    6 publications · 322 citations

    6

    h-index

  5. Artificial Intelligence

    4 publications · 126 citations

    4

    h-index

1–5