DATA IMPUTATION USING AN INTERCONNECTED VARIATIONAL AUTOENCODER MODEL

Embodiments of the present disclosure provide for improved data processing using interconnected variational autoencoder models, which may be used for any of a myriad of purposes. Some embodiments specially train the interconnected variational autoencoder models by utilizing different training scenarios corresponding to presence and/or absence of particular data in a training data set. Particular encoder(s) and/or decoder(s) from the specially trained interconnected variational autoencoder models may then be utilized to improve accuracy of the desired data processing tasks, for example, to generate particular output data.