BriefGPT.xyz
Jul, 2017
潜在高斯过程回归
Latent Gaussian Process Regression
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Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
TL;DR
介绍了一种名为潜在高斯过程回归的方法，可以扩展输入空间，使用潜在变量来调制协方差函数以处理多模态和非平稳过程的回归问题，并在合成数据和实际应用中进行了验证。
Abstract
We introduce
latent gaussian process regression
which is a latent variable extension allowing modelling of
non-stationary
processes using stationary GP priors. The approach is built on extending the input space o
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