Understanding and creating art with AI: Review and outlook
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 …
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
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 …
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
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 …
simultaneous infections and mitigate the disease spreading, which is very relevant to the risk …
Crypto art: A decentralized view
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 …
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
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 …
expression that involves the human body moving through space, performed for the purposes …
20 years of ordinal patterns: Perspectives and challenges
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 …
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
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 …
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) …
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
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 …
applications and is now an essential tool for time series analysis. Beyond becoming a …
Collective dynamics of stock market efficiency
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 …
available information is always confronted with the behavior of real-world markets. While …