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Extracting Low-Dimensional Latent Structure from Time Series in the Presence of Delays
Noisy, high-dimensional time series observations can often be described by a set of low-dimensional latent variables. Commonly-used methods to extract these latent variables typically assume instantaneous relationships between the latent and observed variables. In many physical systems, changes in t...
שמור ב:
| הוצא לאור ב: | Neural Comput |
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| Main Authors: | , , , , |
| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
2015
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4545403/ https://ncbi.nlm.nih.gov/pubmed/26079746 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1162/NECO_a_00759 |
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