activity
20232026
most citedReconstructing supply networks

6 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Differentiable Electricity-Market Clearing for Gradient-Based Planning

Luca Mungo, Maarten P. Scholl, Arnau Quera-Bofarull

Planning a large data center is difficult because a facility big enough to matter changes the electricity prices it will pay. Those prices are set by market clearing, a constrained…

econ.GN2026

Synthetic supply networks

Galvin Ng, Luca Mungo, Damien Bertrand +1

A good representation of the population of firms and households is essential for large-scale economic models. While there exist good methods to create synthetic populations of hous…

physics.soc-ph2025

A differentiable model of supply-chain shocks

Saad Hamid, José Moran, Luca Mungo +2

Modelling how shocks propagate in supply chains is an increasingly important challenge in economics. Its relevance has been highlighted in recent years by events such as Covid-19 a…

econ.GN2023★ 6 cited

Reconstructing supply networks

Luca Mungo, Alexandra Brintrup, Diego Garlaschelli +1

Network reconstruction is a well-developed sub-field of network science, but it has only recently been applied to production networks, where nodes are firms and edges represent cus…

q-fin.ST2023★ 3 cited

Revealing production networks from firm growth dynamics

Luca Mungo, José Moran

We study the correlation structure of firm growth rates. We show that most firms are correlated because of their exposure to a common factor but that firms linked through the suppl…

q-fin.ST2023★ 1 cited

Cryptocurrency co-investment network: token returns reflect investment patterns

Luca Mungo, Silvia Bartolucci, Laura Alessandretti

Since the introduction of Bitcoin in 2009, the dramatic and unsteady evolution of the cryptocurrency market has also been driven by large investments by traditional and cryptocurre…