11 citations · 32 across the 9 of their papers we have counts for
9 papers
Benchmarking Graph Neural Networks in Solving Hard Constraint Satisfaction Problems
Geri Skenderi, Lorenzo Buffoni, Francesco D'Amico +6
Graph neural networks (GNNs) are increasingly applied to hard optimization problems, often claiming superiority over classical heuristics. However, such claims risk being unsolid d…
Algorithmic thresholds in combinatorial optimization depend on the time scaling
M. C. Angelini, M. Avila-González, F. D'Amico +3
In the last decades, many efforts have focused on analyzing typical-case hardness in optimization and inference problems. Some recent work has pointed out that polynomial algorithm…
Local equations describe unreasonably efficient stochastic algorithms in random K-SAT
David Machado, Jonathan González-García, Roberto Mulet
Despite significant advances in characterizing the highly nonconvex landscapes of constraint satisfaction problems, the good performance of certain algorithms in solving hard combi…
Improved mean-field dynamical equations are able to detect the two-steps relaxation in glassy dynamics at low temperatures
David Machado, Roberto Mulet, Federico Ricci-Tersenghi
We study the stochastic relaxation dynamics of the Ising p-spin model on a random graph, a well-known model with glassy dynamics at low temperatures. We introduce and discuss a new…
From random point processes to hierarchical Cavity Master Equations for the stochastic dynamics of disordered systems in Random Graphs: Ising models and epidemics
David Machado, Roberto Mulet
We start from the Theory of Random Point Processes to derive n-point coupled master equations describing the continuous dynamics of discrete variables in random graphs. These equat…
Dynamics of epidemic models from cavity master equations
Ernesto Ortega, David Machado, Alejandro Lage-Castellanos
We apply the cavity master equation (CME) approach to epidemics models. We explore mostly the susceptible-infectious-susceptible (SIS) model, which can be readily treated with the…