Normalizing and Encoding Source Data for an Autoencoder In practice, preparing the source data for an autoencoder is the most time-consuming part of the dimensionality reduction process. To normalize ...

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 ...