Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

We propose an unsupervised method for detecting adversarial attacks in inner layers of autoencoder (AE) networks by maximizing a non-parametric measure of anomalous node activations.

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides. Authors: Farzad Midjani, Hossein Abbasi, Mahdi Malekpour, Shahin Yaghoobi, Sina Abdous, ...