Deep LearningBased Changepoint Detection with Local Neural Models // Implementation of deep learningbased changepoint detection algorithm designed for time series with smooth local fluctuations. The method fits localized feedforward neural networks to approximate the underlying smooth component and constructs a residualbased detector that isolates abrupt structural changes. A fully dataadaptive empirical cumulative distribution function (ECDF) based thresholding rule and refinement procedures yield accurate changepoint localization without parametric assumptions on noise or trend structure.