Maria Chiara Angelini

发表

Monte Carlo algorithms are very effective in finding the largest independent set in sparse random graphs

Federico Ricci-Tersenghi, Maria Chiara Angelini, F. Ricci-Tersenghi, 2019, Physical review. E.

Spectral detection on sparse hypergraphs

Florent Krzakala, Francesco Caltagirone, Lenka Zdeborová, 2015, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Compressed sensing with sparse, structured matrices

Yoshiyuki Kabashima, Federico Ricci-Tersenghi, Maria Chiara Angelini, 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Parallel Tempering for the planted clique problem pdf

Maria Chiara Angelini, 2018, ArXiv.

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, 2021, Journal of Statistical Mechanics: Theory and Experiment.

Entropic long range order in a 3D spin glass model

Maria Chiara Angelini, F. Ricci-Tersenghi, 2010, 1007.1922.

Statistical Physics of Inference and Bayesian Estimation

Maria Chiara Angelini, F. Krzakala, L. Zdeborová, 2015 .

Statistical Physics of Inference problems

Maria Chiara Angelini, F. Krzakala, F. Caltagirone, 2014 .

Solving the spherical p -spin model with the cavity method: equivalence with the replica results

Maria Chiara Angelini, F. Ricci-Tersenghi, L. Leuzzi, 2020, Journal of Statistical Mechanics: Theory and Experiment.

Loop expansion around the Bethe approximation through the M-layer construction

Maria Chiara Angelini, G. Parisi, C. Lucibello, 2017, 1707.08499.

Relations between short-range and long-range Ising models.

Giorgio Parisi, Federico Ricci-Tersenghi, Maria Chiara Angelini, 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

A theory explaining the limits and performances of algorithms based on simulated annealing in solving sparse hard inference problems

Maria Chiara Angelini, F. Ricci-Tersenghi, 2022, Physical Review X.

Cracking nuts with a sledgehammer: when modern graph neural networks do worse than classical greedy algorithms

Maria Chiara Angelini, F. Ricci-Tersenghi, 2022, ArXiv.

Ising spin glass on random graphs at zero temperature: Not all spins are glassy in the glassy phase

Maria Chiara Angelini, G. Parisi, F. Ricci-Tersenghi, 2022, Physical review B.

A pr 2 01 9 Monte Carlo algorithms are very effective in finding the largest independent set in sparse random graphs

Maria Chiara Angelini, F. Ricci-Tersenghi, 2019 .

Ising spin glass on random graphs at zero temperature: Not all spins are glassy in the glassy phase

Maria Chiara Angelini, G. Parisi, F. Ricci-Tersenghi, 2022, Physical Review B.

Spin glass in a field: a new zero-temperature fixed point in finite dimensions.

Maria Chiara Angelini, G. Biroli, 2014, Physical review letters.

Real Space Migdal–Kadanoff Renormalisation of Glassy Systems: Recent Results and a Critical Assessment

Maria Chiara Angelini, G. Biroli, 2017, Journal of Statistical Physics.

Loop expansion around the Bethe solution for the random magnetic field Ising ferromagnets at zero temperature

Maria Chiara Angelini, G. Parisi, C. Lucibello, 2019, Proceedings of the National Academy of Sciences.

Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set

Maria Chiara Angelini, F. Ricci-Tersenghi, 2022, Nature Machine Intelligence.

Real Space Migdal–Kadanoff Renormalisation of Glassy Systems: Recent Results and a Critical Assessment

Maria Chiara Angelini, G. Biroli, 2017, Journal of Statistical Physics.

Solving the fully-connected spherical $p$-spin model with the cavity method: equivalence with the replica results

Maria Chiara Angelini, F. Ricci-Tersenghi, L. Leuzzi, 2020, 2007.01687.

Unexpected Upper Critical Dimension for Spin Glass Models in a Field Predicted by the Loop Expansion around the Bethe Solution at Zero Temperature.

Maria Chiara Angelini, G. Parisi, C. Lucibello, 2021, Physical review letters.

Real space renormalization group theory of disordered models of glasses

Maria Chiara Angelini, G. Biroli, 2016, Proceedings of the National Academy of Sciences.

Ensemble renormalization group for disordered systems

Maria Chiara Angelini, G. Parisi, F. Ricci-Tersenghi, 2011, 1111.6869.

A theory explaining the limits and performances of algorithms based on simulated annealing in solving sparse hard inference problems

Maria Chiara Angelini, F. Ricci-Tersenghi, 2022, Physical Review X.

Super-Potts glass: A disordered model for glass-forming liquids

Maria Chiara Angelini, G. Biroli, 2014, 1407.7393.

Stochastic Gradient Descent-like relaxation is equivalent to Glauber dynamics in discrete optimization and inference problems

Maria Chiara Angelini, F. Ricci-Tersenghi, Raffaele Marino, 2023, Scientific reports.

Loop expansion around the Bethe approximation through the M-layer construction

Maria Chiara Angelini, G. Parisi, C. Lucibello, 2017, 1707.08499.

Real space renormalization group theory of disordered models of glasses

Maria Chiara Angelini, G. Biroli, 2016, Proceedings of the National Academy of Sciences.