BriefGPT.xyz
Jul, 2021
STRODE:随机边界常微分方程
STRODE: Stochastic Boundary Ordinary Differential Equation
HTML
PDF
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
TL;DR
本文提出了一种概率微分方程(STRODE),它可以在不需要任何时间注释的情况下,同时学习时间序列数据的时间和动态。该方法成功地推断了时间序列数据的事件时间,并在合成和实际数据集上实现了与现有技术相当或更好的性能表现。
Abstract
Perception of time from sequentially acquired sensory inputs is rooted in everyday behaviors of individual organisms. Yet, most algorithms for
time-series modeling
fail to learn dynamics of random
event timings
d
→