SYSTEMS AND METHODS FOR LEARNING ACROSS MULTIPLE CHEMICAL SENSING UNITS USING A MUTUAL LATENT REPRESENTATION

摘要

Systems and methods for training models across multiple sensing units in a chemical sensing system are described. The chemical sensing system comprises at least one computer processor and at least one computer readable medium including instructions that, when executed by the at least one computer processor, cause the chemical sensing system to perform a training process. The training process comprises accessing a training dataset including first values representing first signals output from a first chemical sensing unit of multiple chemical sensing units, and second values representing second signals output from a second chemical sensing unit of the multiple chemical sensing units, and training a set of models to relate the first values and the second values to a mutual latent representation using the training dataset.