39 citations · 100 across the 16 of their papers we have counts for
21 papers
Framework based on complex networks to model and mine patient pathways
Caroline de Oliveira Costa Souza Rosa, Márcia Ito, Alex Borges Vieira +2
The automatic discovery of a model to represent the history of encounters of a group of patients with the healthcare system -- the so-called "pathway of patients" -- is a new field…
A Simplicity Bubble Problem in Formal-Theoretic Learning Systems
Felipe S. Abrahão, Hector Zenil, Fabio Porto +3
When mining large datasets in order to predict new data, limitations of the principles behind statistical machine learning pose a serious challenge not only to the Big Data deluge,…
An Algorithmic Information Distortion in Multidimensional Networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
Network complexity, network information content analysis, and lossless compressibility of graph representations have been played an important role in network analysis and network m…
Emergence of complex data from simple local rules in a network game
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
As one of the main subjects of investigation in data science, network science has been demonstrated a wide range of applications to real-world networks analysis and modeling. For e…
On the existence of hidden machines in computational time hierarchies
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
Challenging the standard notion of totality in computable functions, one has that, given any sufficiently expressive formal axiomatic system, there are total functions that, althou…
You Shall not Pass: Avoiding Spurious Paths in Shortest-Path Based Centralities in Multidimensional Complex Networks
Klaus Wehmuth, Artur Ziviani, Leonardo Chinelate Costa +2
In complex network analysis, centralities based on shortest paths, such as betweenness and closeness, are widely used. More recently, many complex systems are being represented by…
Transtemporal edges and crosslayer edges in incompressible high-order networks
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph representation. We study some of their network…
Learning the undecidable from networked systems
Felipe S. Abrahão, Ítala M. Loffredo D'Ottaviano, Klaus Wehmuth +2
This article presents a theoretical investigation of computation beyond the Turing barrier from emergent behavior in distributed systems. In particular, we present an algorithmic n…
Expected Emergence of Algorithmic Information from a Lower Bound for Stationary Prevalence
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
We study emergent information in populations of randomly generated networked computable systems that follow a Susceptible-Infected-Susceptible contagion (or infection) model of imi…
On sequential structures in incompressible multidimensional networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
In order to deal with multidimensional structure representations of real-world networks, as well as with their worst-case irreducible information content analysis, the demand for n…
Algorithmic information distortions and incompressibility in uniform multidimensional networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
This article presents a theoretical investigation of generalized encoded forms of networks in a uniform multidimensional space. First, we study encoded networks with (finite) arbit…
Emergent Open-Endedness from Contagion of the Fittest
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
In this paper, we study emergent irreducible information in populations of randomly generated computable systems that are networked and follow a "Susceptible-Infected-Susceptible"…
A Multilayer and Time-varying Structural Analysis of the Brazilian Air Transportation Network
Bernardo Costa, João Victor Bechara, Klaus Wehmuth +1
This paper provides a multilayer and time-varying structural analysis of one air transportation network, having the Brazilian air transportation network as a case study. Using a si…
Algorithmic Networks: central time to trigger expected emergent open-endedness
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
This article investigates emergence and complexity in complex systems that can share information on a network. To this end, we use a theoretical approach from information theory, c…
Social Events in a Time-Varying Mobile Phone Graph
Carlos Sarraute, Jorge Brea, Javier Burroni +3
The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobi…
MultiAspect Graphs: Algebraic representation and algorithms
Klaus Wehmuth, Éric Fleury, Artur Ziviani
We present the algebraic representation and basic algorithms for MultiAspect Graphs (MAGs). A MAG is a structure capable of representing multilayer and time-varying networks, as we…
Time Centrality in Dynamic Complex Networks
Eduardo Chinelate Costa, Alex Borges Vieira, Klaus Wehmuth +2
There is an ever-increasing interest in investigating dynamics in time-varying graphs (TVGs). Nevertheless, so far, the notion of centrality in TVG scenarios usually refers to metr…
On MultiAspect Graphs
Klaus Wehmuth, Éric Fleury, Artur Ziviani
Different graph generalizations have been recently used in an ad-hoc manner to represent multilayer networks, i.e. systems formed by distinct layers where each layer can be seen as…
A Unifying Model for Representing Time-Varying Graphs
Klaus Wehmuth, Artur Ziviani, Eric Fleury
Graph-based models form a fundamental aspect of data representation in Data Sciences and play a key role in modeling complex networked systems. In particular, recently there is an…
DANCE: A Framework for the Distributed Assessment of Network Centralities
Klaus Wehmuth, Antonio Tadeu A. Gomes, Artur Ziviani
The analysis of large-scale complex networks is a major challenge in the Big Data domain. Given the large-scale of the complex networks researchers commonly deal with nowadays, the…
Distributed Algorithm to Locate Critical Nodes to Network Robustness based on Spectral Analysis
Klaus Wehmuth, Artur Ziviani
We propose an algorithm to locate the most critical nodes to network robustness. Such critical nodes may be thought of as those most related to the notion of network centrality. Ou…