Autoencoder networks: the core of the attentional autoencoder network is the autoencoder. An autoencoder is a neural network structure that consists of an encoder and a decoder.

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 ...

The Data Science Lab Data Anomaly Detection Using a Neural Autoencoder with C# 04/15/2024 Get Code Download Data anomaly detection is the process of examining a set of source data to find data items ...

Ziwei Zhu, Assistant Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “III: Small: Harnessing Interpretable Neuro-Symbolic Learning for ...