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Kejin Wu

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Open access Aug 2026

Exploratory Continuous-Time Modeling (Expct): Extracting Dynamic Features from Irregularly Spaced Time Series.

When collecting intensive longitudinal data in the social, behavioral and biomedical sciences irregularly spaced data (i.e., data that are not collected at equal intervals) are the norm rather than the exception. However, most of the techniques and models that are used to analyze these data in practice were designed fo...

Oisín Ryan, Kejin Wu, Nicholas C. Jacobson · 0 citations
Preprint Aug 2026

Prediction Inference of Time Series with Standard ReLU Deep Neural Networks

This work proposes a methodology based on the standard ReLU Deep Neural Networks (DNN) to make predictions and quantify their uncertainty, and builds the so-called pertinent prediction interval (PPI) with the DNN model estimator.

Kejin Wu · 0 citations

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