Universal Functional Regression with Neural Operator Flows

Regression on function spaces is typically limited to models with Gaussian process priors. We introduce the notion of universal functional regression, in which we aim to learn a prior distribution over non-Gaussian function spaces that remains mathematically tractable for functional regression. To d...

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Veröffentlicht in:	arXiv.org 2024-11
Hauptverfasser:	Shi, Yaozhong, Gao, Angela F, Ross, Zachary E, Azizzadenesheli, Kamyar
Format:	Artikel
Sprache:	eng
Schlagworte:	Function space Gaussian process Mathematical analysis Normal distribution Regression Robustness (mathematics)
Online-Zugang:	Volltext
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