2 citations · 2 across the 3 of their papers we have counts for
3 papers
Data+Shift: Supporting visual investigation of data distribution shifts by data scientists
João Palmeiro, Beatriz Malveiro, Rita Costa +3
Machine learning on data streams is increasingly more present in multiple domains. However, there is often data distribution shift that can lead machine learning models to make inc…
GUDIE: a flexible, user-defined method to extract subgraphs of interest from large graphs
Maria Inês Silva, David Aparício, Beatriz Malveiro +2
Large, dense, small-world networks often emerge from social phenomena, including financial networks, social media, or epidemiology. As networks grow in importance, it is often nece…
Finding NeMo: Fishing in banking networks using network motifs
Xavier Fontes, David Aparício, Maria Inês Silva +3
Banking fraud causes billion-dollar losses for banks worldwide. In fraud detection, graphs help understand complex transaction patterns and discovering new fraud schemes. This work…