2024
DOI: 10.3390/bs14070527
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Exploring the Potential of Variational Autoencoders for Modeling Nonlinear Relationships in Psychological Data

Nicola Milano,
Monica Casella,
Raffaella Esposito
et al.

Abstract: Latent variables analysis is an important part of psychometric research. In this context, factor analysis and other related techniques have been widely applied for the investigation of the internal structure of psychometric tests. However, these methods perform a linear dimensionality reduction under a series of assumptions that could not always be verified in psychological data. Predictive techniques, such as artificial neural networks, could complement and improve the exploration of latent space, overcoming … Show more

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