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
Parents
139
Hidden Variables, Joint Probability, and the Bell Inequalities
Arthur Fine · Physical Review Letters · 1982 · 1.2K citations
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195
University of California, Berkeley
Berkeley, United States
5 h-index
9 publications
742 citations
National University of Singapore
Singapore, Singapore
3 h-index
13 publications
632 citations

Newcastle University
Newcastle upon Tyne, United Kingdom
3 h-index
6 publications
354 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
4 publications
566 citations

Ocean University of China
Qingdao, China
3 h-index
10 publications
127 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
6 publications
247 citations
Tsinghua University
Beijing, China
3 h-index
3 publications
89 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
5 publications
91 citations
1–8 of 195
4 publications · 278 citations
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PRL · 4 publications · 1.4K citations
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PRA · 4 publications · 93 citations
4
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3 publications · 146 citations
3
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2 publications · 39 citations
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1–5