Neural Sequence Model is a computational model within the class of neural networks that uniquely processes and predicts sequential data by leveraging internal state representations to capture temporal dependencies across ordered input elements.
359
Publications
133.2K
Citations
1.1K
Authors
346
Institutions
Publications per year
2017–2026
254
Parents
Publications
359
Sepp Hochreiter, Jürgen Schmidhuber · Neural Computation · 1997 · 98.1K citations
Generating Text with Recurrent Neural Networks
Ilya Sutskever, James Martens, Geoffrey E. Hinton · 2011 · 1.2K citations
1–5 of 359
Authors
1.1K
- YB
8
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- VK
6
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- JZ
6
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- SB
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- GN
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Institutions
346
Google (United States)
Mountain View, United States
17 h-index
65 publications
8.5K citations
Carnegie Mellon University
Pittsburgh, United States
9 h-index
20 publications
1.7K citations
Stanford University
Stanford, United States
8 h-index
14 publications
1.9K citations
Microsoft (United States)
Redmond, United States
8 h-index
23 publications
2K citations
University of Washington
Seattle, United States
7 h-index
24 publications
791 citations
Massachusetts Institute of Technology
Cambridge, United States
6 h-index
7 publications
679 citations
University of Oxford
Oxford, United Kingdom
6 h-index
17 publications
5.2K citations
University of Edinburgh
Edinburgh, United Kingdom
6 h-index
12 publications
870 citations
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Venues
- arXiv (Cornell University)
Repository · 100 publications · 12.7K citations
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- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 11 publications · 888 citations
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- Neurocomputing
6 publications · 135 citations
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- IEEE Access
5 publications · 541 citations
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- Neural Information Processing Systems
Conference · 5 publications · 196 citations
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