MULTITASK LEARNING BASED ON HERMITIAN OPERATORS
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United States of America Patent
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Issued Date -
Feb 15, 2024
app pub date -
Aug 9, 2022
filing date -
Aug 9, 2022
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Abstract
A method for multitask learning based on Hermitian operators is described. The method includes training a multitask machine learning (MTML) model to map an input representation of a material onto a complex wave function state vector. The method also includes inferring, by a trained, MTML model, observable property matrices for each observable property of the material. The method further includes converting the observable property matrices into complex Hermitian operators. The method also includes predicting target properties of the material according to the complex Hermitian operators and the complex wave function state vector.
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