Slepian-wolf Coding
Slepian-Wolf Coding is a theoretical framework in lossless data compression that enables distributed source coding of correlated information sources without inter-source communication, achieving joint entropy rates as if the sources were encoded together.
290
Publications
19.2K
Citations
435
Authors
219
Institutions
Publications per year
2017–2026
16
290
A Random Linear Network Coding Approach to Multicast
T. Ho, Muriel Médard, R. Koetter et al. · IEEE Transactions on Information Theory · 2006 · 2.6K citations
Bernd Girod, A. Aaron, Shantanu Rane et al. · Proceedings of the IEEE · 2004 · 1.3K citations
1–5 of 290
435
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IBM Research - Thomas J. Watson Research Center, United States
12 publications · 268 citations
11
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1–5 of 435
219
Texas A&M University
College Station, United States
24 h-index
107 publications
10.7K citations
California Institute of Technology
Pasadena, United States
13 h-index
24 publications
6.4K citations
University of California, Berkeley
Berkeley, United States
11 h-index
19 publications
1.3K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
11 h-index
26 publications
758 citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
27 publications
11.3K citations
Stanford University
Stanford, United States
11 h-index
30 publications
7.2K citations
University of Delaware
Newark, United States
9 h-index
16 publications
1.1K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
8 h-index
20 publications
586 citations
1–8 of 219
54 publications · 6.7K citations
31
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15 publications · 430 citations
12
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10 publications · 1.4K citations
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Repository · 5 publications · 204 citations
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4 publications · 191 citations
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