111 citations · 180 across the 10 of their papers we have counts for
10 papers
Studying and Improving Graph Neural Network-based Motif Estimation
Pedro C. Vieira, Miguel E. P. Silva, Pedro Manuel Pinto Ribeiro
Graph Neural Networks (GNNs) are a predominant method for graph representation learning. However, beyond subgraph frequency estimation, their application to network motif significa…
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…
From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs
Ahmad Naser Eddin, Jacopo Bono, David Aparício +4
Many real-world datasets have an underlying dynamic graph structure, where entities and their interactions evolve over time. Machine learning models should consider these dynamics…
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…