Adiabatic quenches through an extended quantum critical region F Pellegrini, S Montangero, GE Santoro, R Fazio Physical Review B 77 (14), 140404, 2008 | 67 | 2008 |

Giant frictional dissipation peaks and charge-density-wave slips at the NbSe_{2} surfaceM Langer, M Kisiel, R Pawlak, F Pellegrini, GE Santoro, R Buzio, A Gerbi, ... Nature materials 13 (2), 173-177, 2014 | 63 | 2014 |

PANNA: Properties from artificial neural network architectures R Lot, F Pellegrini, Y Shaidu, E Küçükbenli Computer Physics Communications 256, 107402, 2020 | 42 | 2020 |

Noncontact Atomic Force Microscope Dissipation Reveals a Central Peak of Structural Phase Transition M Kisiel, F Pellegrini, GE Santoro, M Samadashvili, R Pawlak, A Benassi, ... Physical review letters 115 (4), 046101, 2015 | 26 | 2015 |

Crossover from adiabatic to antiadiabatic quantum pumping with dissipation F Pellegrini, C Negri, F Pistolesi, N Manini, GE Santoro, E Tosatti Physical Review Letters 107 (6), 060401, 2011 | 19 | 2011 |

A systematic approach to generating accurate neural network potentials: The case of carbon Y Shaidu, E Küçükbenli, R Lot, F Pellegrini, E Kaxiras, S de Gironcoli npj Computational Materials 7 (1), 52, 2021 | 16 | 2021 |

An analytic theory of shallow networks dynamics for hinge loss classification F Pellegrini, G Biroli Advances in Neural Information Processing Systems 33, 5356-5367, 2020 | 15 | 2020 |

Fractal fidelity as a signature of quantum chaos F Pellegrini, S Montangero Physical Review A 76 (5), 052327, 2007 | 14 | 2007 |

Frictional lubricity enhanced by quantum mechanics T Zanca, F Pellegrini, GE Santoro, E Tosatti Proceedings of the National Academy of Sciences 115 (14), 3547-3550, 2018 | 12 | 2018 |

Thermally assisted lubricity and negative work tails in sliding friction F Pellegrini, E Panizon, GE Santoro, E Tosatti Physical Review B 99 (7), 075428, 2019 | 10 | 2019 |

Markov state modeling of sliding friction F Pellegrini, FP Landes, A Laio, S Prestipino, E Tosatti Physical Review E 94 (5), 053001, 2016 | 7 | 2016 |

Sifting out the features by pruning: Are convolutional networks the winning lottery ticket of fully connected ones? F Pellegrini, G Biroli arXiv preprint arXiv:2104.13343, 2021 | 6 | 2021 |

Atomic spin-sensitive dissipation on magnetic surfaces F Pellegrini, GE Santoro, E Tosatti Physical review letters 105 (14), 146103, 2010 | 6 | 2010 |

Neural network pruning denoises the features and makes local connectivity emerge in visual tasks F Pellegrini, G Biroli International Conference on Machine Learning, 17601-17626, 2022 | 4 | 2022 |

Friction anomalies at first-order transition spinodals: 1T-TaS2 E Panizon, T Marx, D Dietzel, F Pellegrini, GE Santoro, A Schirmeisen, ... New Journal of Physics 20 (2), 023033, 2018 | 4 | 2018 |

Charge-density-wave surface phase slips and noncontact nanofriction F Pellegrini, GE Santoro, E Tosatti Physical Review B 89 (24), 245416, 2014 | 4 | 2014 |

A Markov state modeling analysis of sliding dynamics of a 2D model M Teruzzi, F Pellegrini, A Laio, E Tosatti The Journal of Chemical Physics 147 (15), 2017 | 2 | 2017 |

Thermolubricity and the Jarzynski equality F Pellegrini, E Panizon, G Santoro, E Tosatti arXiv preprint arXiv:1809.01609, 2018 | 1 | 2018 |

Quantum dissipation at the nanoscale F Pellegrini SISSA, 2011 | 1 | 2011 |

Dynamics of a Quantum Phase Transition in the XXZ Model F Pellegrini | 1 | 2007 |