A new convolutional variational deep embedding model learns a generative latent manifold of EEG microstate topographies, ...

A hybrid deep learning framework that combines ant colony optimization with a spatio-temporal variational autoencoder ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

A research team led by Gergő Orbán at the HUN-REN Wigner Physics Research Center, working with Argentine researchers, has ...

Autoencoders are a common tool for training neural network algorithms, but developers need to be mindful of the challenges that come with using them skillfully. Autoencoders are additional neural ...