Learn Before
Definition

Stationary Dynamics

In sequence modeling, stationary dynamics refer to a modeling assumption where the underlying rules governing how each observation is generated from previous observations do not change over time. While the specific observed values xtx_t may fluctuate from step to step, the conditional distribution P(xtxt1,)P(x_t \mid x_{t-1}, \ldots) that governs the generation process remains constant. This stationarity assumption is crucial because it allows historical sequence data to be meaningfully used as training examples for predicting future events—if the dynamics changed, patterns learned from old data would not generalize to new data.

0

1

Updated 2026-05-13

Contributors are:

Who are from:

Tags

D2L

Dive into Deep Learning @ D2L

Related