Information Divergence
Information Divergence is a measure of discrepancy between two probability distributions that belongs to the class of statistical distance measures, distinguished by its foundation in information theory and its quantification of the relative entropy or inefficiency arising from assuming one distribution over another.
491
Publications
40.8K
Citations
830
Authors
499
Institutions
Publications per year
2017–2026
124
Variants
Information-theoretic Divergence
Parents
491
1–5 of 491
830
11
h-index
Czech Academy of Sciences, Institute of Information Theory and Automation, Czechia
11 publications · 954 citations
11
h-index
10
h-index
10
h-index
7
h-index
1–5 of 830
499
Czech Academy of Sciences, Institute of Information Theory and Automation
Prague, Czechia
11 h-index
11 publications
920 citations
University of Michigan
Ann Arbor, United States
10 h-index
14 publications
568 citations
Sony Computer Science Laboratories
Tokyo, Japan
9 h-index
9 publications
558 citations
University of Maryland, Baltimore County
Baltimore, United States
8 h-index
9 publications
1.5K citations
Princeton University
Princeton, United States
8 h-index
10 publications
777 citations
Technion – Israel Institute of Technology
Haifa, Israel
8 h-index
10 publications
976 citations

Centre National de la Recherche Scientifique
Paris, France
7 h-index
11 publications
259 citations

Consejo Nacional de Investigaciones Científicas y Técnicas
Buenos Aires, Argentina
7 h-index
18 publications
986 citations
1–8 of 499
53 publications · 13K citations
33
h-index
27 publications · 1.5K citations
20
h-index
Repository · 15 publications · 417 citations
12
h-index
10 publications · 364 citations
10
h-index
7 publications · 145 citations
7
h-index
1–5