连续时间非线性状态空间模型的变分推理与学习][Variational inference and learning for continuous-time nonlinear state-space models]

连续时间非线性状态空间模型的变分推理与学习 Variational inference and learning for continuous-time nonlinear state-space models


课程网址:	http://videolectures.net/aispds08_raiko_vil/
主讲教师:	Tapani Raiko
开课单位:	阿尔托大学
开课时间:	2008-08-05
课程语种:	英语
中文简介:	连续时间随机动力模型的推理是一个具有挑战性的问题。为了补充现有的基于采样的方法，变分方法最近被开发出来解决这个问题。我们的方法通过离散化来解决变分连续时间推理问题，本质上将其简化为离散时间问题。我们的框架使模型的学习和推理更加容易。其他扩展，如异方差模型，在这个框架中也相对容易考虑。
课程简介:	Inference in continuous-time stochastic dynamical models is a challenging problem. To complement existing sampling-based methods, variational methods have recently been developed for this problem. Our approach solves the variational continuous-time inference problem by discretisation that essentially reduces it to a discrete-time problem. Our framework makes learning the model in addition to inference easy. Other extensions such as heteroscedastic models are also relatively easy to consider within this framework.
关键词:	连续时间; 非线性状态; 空间模型; 变分推理
课程来源:	视频讲座网
最后编审:	2021-01-31：nkq
阅读次数:	32

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