Gaussian Network Models is a mathematical framework in Network Information Theory that characterizes communication networks with additive white Gaussian noise channels, distinguished by its use of jointly Gaussian input and output signal distributions to analyze fundamental limits of information transmission under power and noise constraints.
184
Publications
9.7K
Citations
460
Authors
241
Institutions
Publications per year
2017–2026
36
Parents
Publications
184
On-line EM Algorithm for the Normalized Gaussian Network
Masa-aki Sato, Shin Ishii · Neural Computation · 2000 · 280 citations
1–5 of 184
Authors
460
- İB
11
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- BE
11
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- TH
10
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- RL
5
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5
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1–5 of 460
Institutions
241
Boğaziçi University
Istanbul, Türkiye
14 h-index
36 publications
2.2K citations
Koç University
Istanbul, Türkiye
11 h-index
26 publications
804 citations
University of Pittsburgh
Pittsburgh, United States
8 h-index
27 publications
2.7K citations
Tel Aviv University
Tel Aviv, Israel
6 h-index
8 publications
150 citations
University of California, Berkeley
Berkeley, United States
6 h-index
7 publications
1K citations
Technion – Israel Institute of Technology
Haifa, Israel
5 h-index
8 publications
682 citations
National Cancer Institute
Bethesda, United States
5 h-index
12 publications
1.2K citations
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Ankara, Türkiye
5 h-index
10 publications
1.4K citations
1–8 of 241
Venues
- Proteins Structure Function and Bioinformatics
15 publications · 992 citations
13
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- IEEE Transactions on Information Theory
13 publications · 1.8K citations
13
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- The Journal of Chemical Physics
7 publications · 539 citations
7
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- Nucleic Acids Research
5 publications · 461 citations
5
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- PLoS ONE
5 publications · 114 citations
5
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1–5