Inter-domain deep Gaussian processes
Inter-domain Gaussian processes (GPs) allow for high flexibility and low computational cost when performing approximate inference in GP models. They are particularly suitable for modeling data exhibiting global structure but are limited to stationary covariance functions and thus fail to model non-s...
| Autors principals: | , , |
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| Format: | Conference item |
| Idioma: | English |
| Publicat: |
Proceedings of Machine Learning Research
2020
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