A robust autoencoder uses a special objective function, correntropy, a localized similarity measure which makes it less sensitive to noise in data. Correntropy specifically measures the probability density that two events are equal, and is less affected by outliers than the mean squared error.

autoencoder_robust(network, sigma = 0.2)

## Arguments

network Layer construct of class "ruta_network" Sigma parameter in the kernel used for correntropy

## Value

A construct of class "ruta_autoencoder"

## References

Other autoencoder variants: autoencoder_contractive, autoencoder_denoising, autoencoder_sparse, autoencoder_variational, autoencoder