#P-complete Problems

#P-Complete Problems is a complexity class comprising computational problems that are at least as hard as the hardest problems in #P, where a problem is #P-complete if it is in #P and every problem in #P can be reduced to it via a polynomial-time counting reduction.

43

Publications

5.1K

Citations

74

Authors

49

Institutions

Publications per year

2017–2026

5

Authors

74

  1. JC
    Jin‐Yi Cai

    University of Wisconsin–Madison, United States

    3 publications · 103 citations

    3

    h-index

  2. LG
    Leslie G. Valiant

    Harvard University, United States

    3 publications · 2.3K citations

    3

    h-index

  3. FP
    Francesco Parisi

    University of Calabria, Italy

    2 publications · 115 citations

    2

    h-index

  4. MH
    Mark Huber

    Duke University, United States

    2 publications · 29 citations

    2

    h-index

  5. SF
    Sergio Flesca

    University of Calabria, Italy

    2 publications · 115 citations

    2

    h-index

1–5 of 74

Venues

  1. SIAM Journal on Computing

    4 publications · 2.4K citations

    4

    h-index

  2. Journal of Computer and System Sciences

    3 publications · 81 citations

    3

    h-index

  3. Theoretical Computer Science

    2 publications · 82 citations

    2

    h-index

  4. International Joint Conference on Artificial Intelligence

    Conference · 2 publications · 81 citations

    2

    h-index

  5. Random Structures and Algorithms

    2 publications · 41 citations

    2

    h-index

1–5