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History Marginalization Improves Forecasting in Variational Recurrent Neural Networks
Deep probabilistic time series forecasting models have become an integral part of machine learning. While several powerful generative models have been proposed, we provide evidence that their associated inference models are oftentimes too limited and cause the generative model to predict mode-averag...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8700018/ https://www.ncbi.nlm.nih.gov/pubmed/34945869 http://dx.doi.org/10.3390/e23121563 |