BriefGPT.xyz
Jun, 2014
变分高斯过程状态空间模型
Variational Gaussian Process State-Space Models
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Roger Frigola, Yutian Chen, Carl E. Rasmussen
TL;DR
该论文介绍了利用稀疏高斯过程进行非线性状态空间建模的高效变分贝叶斯学习的过程，以及后续的可处理的非线性动态系统建模、模型容量和计算成本的平衡、避免过度拟合以及使用混合推理方法（变分贝叶斯和顺序蒙特卡洛）进行主算法等。
Abstract
state-space models
have been successfully used for more than fifty years in different areas of science and engineering. We present a procedure for efficient
variational bayesian learning
of nonlinear
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