Shannon Entropy
Shannon Entropy is an information measure that quantifies the average level of uncertainty or information content associated with the outcomes of a random variable by computing the expected value of the logarithmic probabilities of its possible states.
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219.2K
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Publications per year
2017–2026
1.5K
Variants
Information Entropy
4.1K
Altered fecal microbiota composition in patients with major depressive disorder
Hai‐yin Jiang, Yonghua Zhang, Hongjin Mao et al. · Brain Behavior and Immunity · 2015 · 2.3K citations · Full text
On the Shannon capacity of a graph
László Lovász · IEEE Transactions on Information Theory · 1979 · 1.7K citations
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University of Electronic Science and Technology of China, China
18 publications · 972 citations
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Centre National de la Recherche Scientifique
Paris, France
27 h-index
61 publications
3.2K citations

Universidad de Granada
Granada, Spain
26 h-index
44 publications
2K citations

Universidad Autónoma Metropolitana
Mexico City, Mexico
24 h-index
33 publications
1.2K citations
Stanford University
Stanford, United States
22 h-index
29 publications
2.2K citations
Massachusetts Institute of Technology
Cambridge, United States
21 h-index
24 publications
2.8K citations

Chinese Academy of Sciences
Beijing, China
20 h-index
31 publications
1.1K citations
Tsinghua University
Beijing, China
19 h-index
29 publications
1.3K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
18 h-index
26 publications
1.4K citations
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155 publications · 26.4K citations
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242 publications · 8.9K citations
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PRA · 45 publications · 3.5K citations
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Repository · 60 publications · 2.6K citations
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PRL · 33 publications · 3.7K citations
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