19 citations · 74 across the 8 of their papers we have counts for
9 papers
Generalized contact matrices for epidemic modeling
Adriana Manna, Lorenzo Dall'Amico, Michele Tizzoni +2
Contact matrices have become a key ingredient of modern epidemic models. They account for the stratification of contacts for the age of individuals and, in some cases, the context…
Comparing temporal and aggregated network descriptions of fluid transport in the Mediterranean Sea
Kishor Acharya, Javier Aguilar, Lorenzo Dall'Amico +3
Ocean currents exhibit strong time dependence at all scales that influences physical and biochemical dynamics. Network approaches to fluid transport permit to address explicitly ho…
Estimating household contact matrices structure from easily collectable metadata
Lorenzo Dall'Amico, Jackie Kleynhans, Laetitia Gauvin +9
Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age grou…
Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphs
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
This article unveils a new relation between the Nishimori temperature parametrizing a distribution P and the Bethe free energy on random Erdos-Renyi graphs with edge weights distri…
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
This article considers the problem of community detection in sparse dynamical graphs in which the community structure evolves over time. A fast spectral algorithm based on an exten…
A unified framework for spectral clustering in sparse graphs
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
This article considers spectral community detection in the regime of sparse networks with heterogeneous degree distributions, for which we devise an algorithm to efficiently retrie…
Optimal Laplacian regularization for sparse spectral community detection
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Regularization of the classical Laplacian matrices was empirically shown to improve spectral clustering in sparse networks. It was observed that small regularizations are preferabl…
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Spectral clustering is one of the most popular, yet still incompletely understood, methods for community detection on graphs. This article studies spectral clustering based on the…
How does latent liquidity get revealed in the limit order book?
Lorenzo Dall'Amico, Antoine Fosset, Jean-Philippe Bouchaud +1
Latent order book models have allowed for significant progress in our understanding of price formation in financial markets. In particular they are able to reproduce a number of st…