Joint Probability Spaces

Joint Probability Spaces is a mathematical framework that extends a single probability space to model the simultaneous occurrence of events in multiple random experiments by defining a combined sample space, sigma-algebra, and probability measure that jointly govern the outcomes of the constituent variables or processes.

139

Publications

8.6K

Citations

366

Authors

195

Institutions

Publications per year

2017–2026

25

Authors

366

  1. MB
    Max B. Mendel

    University of California, Berkeley, United States

    2 publications · 93 citations

    2

    h-index

  2. YH
    Yongfeng Huang

    Tsinghua University, China

    2 publications · 22 citations

    2

    h-index

  3. AS
    Akihito Soeda

    The University of Tokyo, Japan

    2 publications · 117 citations

    2

    h-index

  4. PK
    Paweł Kurzyński

    Adam Mickiewicz University in Poznań, Poland

    2 publications · 117 citations

    2

    h-index

  5. YC
    Yiqiao Cai

    Huaqiao University, China

    2 publications · 22 citations

    2

    h-index

1–5 of 366

Venues

  1. Coastal Engineering

    4 publications · 278 citations

    4

    h-index

  2. Physical Review Letters

    PRL · 4 publications · 1.4K citations

    4

    h-index

  3. Physical Review A

    PRA · 4 publications · 93 citations

    4

    h-index

  4. Ocean Engineering

    3 publications · 146 citations

    3

    h-index

  5. AIP conference proceedings

    2 publications · 39 citations

    2

    h-index

1–5