Machine-learning (ML) techniques and systems are advantageously employed in areas such as psychiatric genetics, and analysis of gene expression. Generative ML may be performed over large datasets to infer new pleiotropic effects of genetic variants in multiple neuropsychiatric diseases. Deep ML may infer information about psychiatric genetics. ML may realize an efficient estimation of multi-disease genetic and environmental correlation matrices. ML may obtaining protein expression data and generating a mapping between the protein expression data and at least one disease. ML may be performed on a data that that jointly models multiple diseases. Quantum processing can be advantageously employed in ML scenarios.
SYSTEMS AND METHODS FOR GENERATIVE MACHINE LEARNING