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20212026
most citedFast and scalable likelihood maximization for Exponential Random Graph Models with local constraints

51 citations · 107 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Depressive symptoms are reflected differently across digital contexts

Yajing Wang, Emilia Marchese, Talayeh Aledavood +1

As more of everyday life takes place online, digital behavior may provide a potential window into how depressive symptoms are reflected in daily life. Yet digital mental health stu…

physics.soc-ph2024

Spectral signatures of structural change in financial networks

Valentina Macchiati, Emiliano Marchese, Piero Mazzarisi +2

The level of systemic risk in economic and financial systems is strongly determined by the structure of the underlying networks of interdependent entities that can propagate shocks…

physics.soc-ph2021★ 31 cited

Reconstructing firm-level interactions: the Dutch input-output network

Leonardo Niccolò Ialongo, Camille de Valk, Emiliano Marchese +4

Recent crises have shown that the knowledge of the structure of input-output networks at the firm level is crucial when studying economic resilience from the microscopic point of v…

physics.soc-ph2021★ 25 cited

The Weighted Bitcoin Lightning Network

Jian-Hong Lin, Emiliano Marchese, Claudio J. Tessone +1

The Bitcoin Lightning Network (BLN) was launched in 2018 to scale up the number of transactions between Bitcoin owners. Although several contributions concerning the analysis of th…

physics.data-an2021★ 51 cited

Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints

Nicolò Vallarano, Matteo Bruno, Emiliano Marchese +5

Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed for re…