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 ...

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 ...

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

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.