activity
20232025
most citedUnsupervised Learning via Network-Aware Embeddings

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

physics.soc-ph2025

The Economic Complexity of the Roman Empire

Matteo Mazzamurro, Petra Hermankova, Michele Coscia +1

Economic complexity is a powerful tool to estimate the productive capabilities and future growth of modern economies. Little is known of how economic complexity evolves over long p…

physics.soc-ph2024

"A network of mutualities of being": socio-material archaeological networks and biological ties at Çatalhöyük

Camilla Mazzucato, Michele Coscia, Ayça Küçükakdağ Doğu +4

Recent advances in archaeogenomics have granted access to previously unavailable biological information with the potential to further our understanding of past social dynamics at a…

cs.SI2024

Pearson Correlations on Networks: Corrigendum

Michele Coscia, Karel Devriendt

Recently, the first author proposed a measure to calculate Pearson correlations for node values expressed in a network, by taking into account distances or metrics defined on the n…

cs.SI2023

Fast Node Vector Distance Computations using Laplacian Solvers

Michele Coscia, Karel Devriendt

Complex networks are a useful tool to investigate various phenomena in social science, economics, and logistics. Node Vector Distance (NVD) is an emerging set of techniques allowin…

cs.LG20232 cited

Unsupervised Learning via Network-Aware Embeddings

Anne Sophie Riis Damstrup, Sofie Tosti Madsen, Michele Coscia

Data clustering, the task of grouping observations according to their similarity, is a key component of unsupervised learning -- with real world applications in diverse fields such…