AutoClass integrates a classifier to a regular autoencoder, as to fully reconstruct scRNA-Seq data. a AutoClass consists a regular autoencoder and a classifier branch from the bottleneck layer.

Facebook has combined an “adversarial autoencoder” and a “trained-face classifier”. An autoencoder is an artificial neural network that learns a representation for a set of data unsupervised.

Training a Variational Autoencoder Training a VAE involves two measures of similarity (or equivalently measures of loss). First, you must measure how closely the reconstructed output matches the ...

And there are specialized techniques for working with specific types of data, such as fraud detection systems. That said, applying a neural autoencoder anomaly detection system to tabular data is ...

These altered inputs create a security risk in applications with real-world consequences, such as self-driving cars, robotics and financial services. We propose an unsupervised method for detecting ...