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Jul, 2024
具有随机变分推断的可扩展多输出高斯过程
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
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Xiaoyu Jiang, Sokratia Georgaka, Magnus Rattray, Mauricio A. Alvarez
TL;DR
多输出高斯过程是建模来自多个来源的数据的流行工具，本文提出了LV-MOGP的随机变分推断方法，使得计算复杂度与输出数量无关。
Abstract
The
multi-output gaussian process
is is a popular tool for modelling data from multiple sources. A typical choice to build a covariance function for a MOGP is the
linear model of coregionalization
(LMC) which par
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