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Sparse representations of high dimensional neural data
Abstract Conventional Vector Autoregressive (VAR) modelling methods applied to high dimensional neural time series data result in noisy solutions that are dense or have a large number of spurious coefficients. This reduces the speed and accuracy of auxiliary computations downstream and inflates the...
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| Huvudupphovsmän: | , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Nature Portfolio
2022-05-01
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| Serie: | Scientific Reports |
| Länkar: | https://doi.org/10.1038/s41598-022-10459-7 |
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