Mika Sipilä

Enhancing Identifiable Variational Autoencoder in the Presence of Missing Values and Auxiliary Covariates for Spatio‐Temporal Ozone Modeling

Novel identifiable variational autoencoder (iVAE)‐based methods are introduced that explicitly integrate satellite‐derived predictors and handle missing values within a nonlinear blind source separation framework to establish nonlinear blind source separation as a promising approach for spatio‐temporal prediction of en...