Explainable Gaussian processes: a loss landscape perspective

Prior beliefs about the latent function to shape inductive biases can be incorporated into a Gaussian process (GP) via the kernel. However, beyond kernel choices, the decision-making process of GP models remains poorly understood. In this work, we contribute an analysis of the loss landscape for GP...

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Detalles Bibliográficos

Principais autores:	Maximilian P Niroomand, Luke Dicks, Edward O Pyzer-Knapp, David J Wales
Formato:	Artigo
Idioma:	Inglês
Publicado:	IOP Publishing 2024-01-01
Series:	Machine Learning: Science and Technology
Assuntos:	loss landscapes Gaussian processes machine learning physics-inspired
Acceso en liña:	https://doi.org/10.1088/2632-2153/ad62ad
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