46 citations · 48 across the 5 of their papers we have counts for
6 papers
Synthetic Time Series Generation via Complex Networks
Jaime Vale, Vanessa Freitas Silva, Maria Eduarda Silva +1
Time series data are essential for a wide range of applications, yet access to high-quality datasets is often constrained by privacy concerns, acquisition costs, and labelling chal…
Multilayer Quantile Graph for Multivariate Time Series Analysis and Dimensionality Reduction
Vanessa Freitas Silva, Maria Eduarda Silva, Pedro Ribeiro +1
In recent years, there has been a surge in the prevalence of high- and multi-dimensional temporal data across various scientific disciplines. These datasets are characterized by th…
Multilayer Horizontal Visibility Graphs for Multivariate Time Series Analysis
Vanessa Freitas Silva, Maria Eduarda Silva, Pedro Ribeiro +1
Multivariate time series analysis is a vital but challenging task, with multidisciplinary applicability, tackling the characterization of multiple interconnected variables over tim…
Time Series Analysis via Network Science: Concepts and Algorithms
Vanessa Freitas Silva, Maria Eduarda Silva, Pedro Ribeiro +1
There is nowadays a constant flux of data being generated and collected in all types of real world systems. These data sets are often indexed by time, space or both requiring appro…
Novel Features for Time Series Analysis: A Complex Networks Approach
Vanessa Freitas Silva, Maria Eduarda Silva, Pedro Ribeiro +1
Being able to capture the characteristics of a time series with a feature vector is a very important task with a multitude of applications, such as classification, clustering or fo…
GoT-WAVE: Temporal network alignment using graphlet-orbit transitions
David Aparício, Pedro Ribeiro, Tijana Milenković +1
Global pairwise network alignment (GPNA) aims to find a one-to-one node mapping between two networks that identifies conserved network regions. GPNA algorithms optimize node conser…