Sequence Embedding
Sequence Embedding is a representational method that maps sequential data into a structured, lower-dimensional space while preserving inherent temporal or ordinal relationships among elements in the sequence.
69
Publications
4.9K
Citations
221
Authors
94
Institutions
Publications per year
2017–2026
49
Parents
69
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
Adam P. Roberts, Jesse Engel, Colin Raffel et al. · arXiv (Cornell University) · 2018 · 259 citations · Full text
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University of California, Berkeley, United States
3 publications · 128 citations
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2
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1–5 of 221
94
Helmholtz Centre for Infection Research
Braunschweig, Germany
3 h-index
6 publications
256 citations
University of California, Berkeley
Berkeley, United States
3 h-index
6 publications
256 citations
Google (United States)
Mountain View, United States
3 h-index
6 publications
582 citations
Biology of Infection
Paris, France
2 h-index
4 publications
94 citations
Friedrich Schiller University Jena
Jena, Germany
2 h-index
2 publications
63 citations

Lawrence Berkeley National Laboratory
Berkeley, United States
2 h-index
2 publications
112 citations
Tianjin University of Science and Technology
Tianjin, China
2 h-index
2 publications
101 citations
University of Bonn
Bonn, Germany
2 h-index
4 publications
178 citations
1–8 of 94
Repository · 5 publications · 397 citations
5
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Repository · 3 publications · 58 citations
4
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3 publications · 269 citations
3
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Conference · 2 publications · 100 citations
2
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1 publications · 141 citations
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