从数据学习动力系统：一种简单的交叉验证视角
机器学习
2021-04-07 v1 动力系统
混沌动力学
统计计算
机器学习
摘要
从有限个观测状态回归动力系统的向量场，是学习此类系统代理模型的一种自然方式。我们提出交叉验证的变体（Kernel Flows \cite{Owhadi19} 及其基于最大均值差异与Lyapunov指数的变体）作为学习这些仿真器中所用核的简单方法。
引用
@article{arxiv.2007.05074,
title = {Learning dynamical systems from data: a simple cross-validation perspective},
author = {Boumediene Hamzi and Houman Owhadi},
journal= {arXiv preprint arXiv:2007.05074},
year = {2021}
}
备注
File uploaded on arxiv on Sunday, July 5th, 2020. Got delayed due to tex problems on ArXiv. Original version at https://www.researchgate.net/publication/342693818_Learning_dynamical_systems_from_data_a_simple_cross-validation_perspective