There are research efforts to complement an autoencoder with an advanced type of autoencoder called a variational autoencoder (VAE). VAEs tend to underfit so the idea is to combine a basic autoencoder ...

Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk ...