Improving Deep Interactive Evolution with a Style-Based Generator for Artistic Expression and Creative Exploration.

Deep interactive evolution (DeepIE) combines the capacity of interactive evolutionary computation (IEC) to capture a user's preference with the domain-specific robustness of a trained generative adversarial network (GAN) generator, allowing the user to control the GAN output through evolutionary exploration of the latent space. However, the traditional GAN latent space presents feature entanglement, which limits the practicability of possible applications of DeepIE. In this paper, we implement DeepIE within a style-based generator from a StyleGAN model trained on the WikiArt dataset and propose StyleIE, a variation of DeepIE that takes advantage of the secondary disentangled latent space in the style-based generator.

A Community Perspective on Resilience Analytics: A Visual Analysis of Community Mood.

Social networks are ubiquitous in everyday life. Although commonly analyzed from a perspective of individual interactions, social networks can provide insights about the collective behavior of a community. It has been shown that changes in the mood of social networks can be correlated to economic trends, public demonstrations, and political reactions, among others.

State and parameter estimation of a neural mass model from electrophysiological signals during the status epilepticus.

Status epilepticus is an emergency condition in patients with prolonged seizure or recurrent seizures without full recovery between them. The pathophysiological mechanisms of status epilepticus are not well established. With this argument, we use a computational modeling approach combined with in vivo electrophysiological data obtained from an experimental model of status epilepticus to infer about changes that may lead to a seizure.

An algorithm for on-line detection of high frequency oscillations related to epilepsy.

Recent studies suggest that the appearance of signals with high frequency oscillations components in specific regions of the brain is related to the incidence of epilepsy. These oscillations are in general small in amplitude and short in duration, making them difficult to identify. The analysis of these oscillations are particularly important in epilepsy and their study could lead to the development of better medical treatments.