A novelty detection task involves identifying whether a data point is an outlier, given a training dataset that primarily captures the distribution of inliers. The novel class is usually absent, ...

To address these challenges, a novel automated adversarial deep learning-based unsupervised anomaly detection method called EvoAAE is proposed to optimize the hyperparameters and neural architectures ...

Supervised Adversarial Autoencoder Our model for conditional generation is based on a Supervised Adversarial Autoencoder (Supervised AAE, SAAE) (Makhzani et al., 2015) shown in Figure 1. The ...

Let's explore the potential adversarial attacks on AI systems, the security challenges they pose and solutions on how to navigate this landscape and keep models secure.

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.

Insilico Medicine presented an original deep neural network architecture, Entangled Conditional Adversarial Autoencoder (ECAAE), which generates molecular structures based on various properties ...