Neural rough differential equations for long time series
Neural controlled differential equations (CDEs) are the continuous-time analogue of recurrent neural networks, as Neural ODEs are to residual networks, and offer a memory-efficient continuous-time way to model functions of potentially irregular time series. Existing methods for computing the forward...
| Auteurs principaux: | , , , , |
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| Format: | Conference item |
| Langue: | English |
| Publié: |
Journal of Machine Learning Research
2021
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