Understanding and creating art with AI: Review and outlook

E Cetinic, J She - ACM Transactions on Multimedia Computing …, 2022 - dl.acm.org
Technologies related to artificial intelligence (AI) have a strong impact on the changes of
research and creative practices in visual arts. The growing number of research initiatives …

Ordinal patterns-based methodologies for distinguishing chaos from noise in discrete time series

M Zanin, F Olivares - Communications Physics, 2021 - nature.com
One of the most important aspects of time series is their degree of stochasticity vs. chaoticity.
Since the discovery of chaotic maps, many algorithms have been proposed to discriminate …

An epidemiological model with voluntary quarantine strategies governed by evolutionary game dynamics

MA Amaral, MM de Oliveira, MA Javarone - Chaos, Solitons & Fractals, 2021 - Elsevier
During pandemic events, strategies such as social distancing can be fundamental to reduce
simultaneous infections and mitigate the disease spreading, which is very relevant to the risk …

Crypto art: A decentralized view

M Franceschet, G Colavizza, T Smith, B Finucane… - Leonardo, 2021 - direct.mit.edu
Crypto art is limited-edition digital art, cryptographically registered with a token on a
blockchain. Tokens represent a transparent, auditable origin and provenance for a piece of …

[HTML][HTML] Dance on the brain: enhancing intra-and inter-brain synchrony

JC Basso, MK Satyal, R Rugh - Frontiers in human neuroscience, 2021 - frontiersin.org
Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-
expression that involves the human body moving through space, performed for the purposes …

20 years of ordinal patterns: Perspectives and challenges

I Leyva, JH Martínez, C Masoller, OA Rosso… - Europhysics …, 2022 - iopscience.iop.org
In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the
analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is …

Learning physical properties of liquid crystals with deep convolutional neural networks

HYD Sigaki, EK Lenzi, RS Zola, M Perc, HV Ribeiro - Scientific Reports, 2020 - nature.com
Abstract Machine learning algorithms have been available since the 1990s, but it is much
more recently that they have come into use also in the physical sciences. While these …

Multiscale permutation entropy for two-dimensional patterns

C Morel, A Humeau-Heurtier - Pattern Recognition Letters, 2021 - Elsevier
Complexity measures are important to understand and analyze systems with one
dimensional data. However, extension of these methods to images (two dimensional data) …

ordpy: A Python package for data analysis with permutation entropy and ordinal network methods

AAB Pessa, HV Ribeiro - Chaos: An Interdisciplinary Journal of …, 2021 - pubs.aip.org
Since Bandt and Pompe's seminal work, permutation entropy has been used in several
applications and is now an essential tool for time series analysis. Beyond becoming a …

Collective dynamics of stock market efficiency

LGA Alves, HYD Sigaki, M Perc, HV Ribeiro - Scientific reports, 2020 - nature.com
Summarized by the efficient market hypothesis, the idea that stock prices fully reflect all
available information is always confronted with the behavior of real-world markets. While …