Compressed sensing with sparse, structured matrices. - Maria Chiara Angelini; Federico Ricci-Tersenghi; Yoshiyuki Kabashima (Allerton Conference, 2012)

Spectral detection on sparse hypergraphs. - Maria Chiara Angelini; Francesco Caltagirone; Florent Krzakala; Lenka Zdeborová (Allerton, 2015)

Parallel Tempering for the planted clique problem. - Maria Chiara Angelini (CoRR, 2018)

Monte Carlo algorithms are very effective in finding the largest independent set in sparse random graphs. - Maria Chiara Angelini; Federico Ricci-Tersenghi (CoRR, 2019)

Mismatching as a tool to enhance algorithmic performances of Monte Carlo methods for the planted clique model. - Maria Chiara Angelini; Paolo Fachin; Simone de Feo (CoRR, 2021)

A theory explaining the limits and performances of algorithms based on simulated annealing in solving sparse hard inference problems. - Maria Chiara Angelini; Federico Ricci-Tersenghi (CoRR, 2022)

Cracking nuts with a sledgehammer: when modern graph neural networks do worse than classical greedy algorithms. - Maria Chiara Angelini; Federico Ricci-Tersenghi (CoRR, 2022)

Stochastic Gradient Descent-like relaxation is equivalent to Glauber dynamics in discrete optimization and inference problems. - Maria Chiara Angelini; Angelo Giorgio Cavaliere; Raffaele Marino; Federico Ricci-Tersenghi (CoRR, 2023)

Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set. - Maria Chiara Angelini; Federico Ricci-Tersenghi (Nat. Mac. Intell., 2023)