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Variational Autoencoders

Meaning

Variational Autoencoders (VAEs) are a type of generative neural network model used in machine learning to learn efficient, compressed representations of complex data, such as high-dimensional physiological profiles or genomic sequences. In hormonal health, VAEs are utilized to identify underlying latent variables that govern endocrine status, allowing for the generation of synthetic, yet realistic, physiological data to enhance predictive modeling or to characterize the subtle differences between healthy and dysregulated hormonal states.