Universal Entropy Estimation is a formal method in information theory that, under the framework of universal coding, consistently approximates the entropy rate of a stochastic source without prior knowledge of its underlying distribution by leveraging asymptotically accurate statistical models derived from observed data sequences.
9
Publications
381
Citations
20
Authors
12
Institutions
Publications per year
2017–2026
3
Parents
Publications
9
Empirical Estimation of Information Measures: A Literature Guide
Sergio Verdú · Entropy · 2019 · 62 citations · Full text
1–5 of 9
Authors
20
- SV
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- SR
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- JJ
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- JC
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- SP
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1–5 of 20
Institutions
12
Princeton University
Princeton, United States
2 h-index
6 publications
240 citations
Sogang University
Seoul, South Korea
1 h-index
2 publications
32 citations
University of Manchester
Manchester, United Kingdom
1 h-index
1 publications
98 citations
Nanjing University
Nanjing, China
1 h-index
3 publications
33 citations
Balseiro Institute
Bariloche, Argentina
1 h-index
1 publications
98 citations
Yonsei University
Seoul, South Korea
1 h-index
3 publications
48 citations
University of Florida
Gainesville, United States
1 h-index
2 publications
40 citations
University of Bristol
Bristol, United Kingdom
1 h-index
2 publications
60 citations
1–8 of 12
Venues
- Entropy
2 publications · 82 citations
2
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- IEEE Transactions on Information Theory
1 publications · 70 citations
1
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- Physical Review Letters
PRL · 1 publications · 64 citations
1
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- Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
1 publications · 30 citations
1
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- Journal of High Energy Physics
JHEP · 1 publications · 16 citations
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