C. Lucibello

发表

Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes

Christian Borgs, Carlo Baldassi, Alessandro Ingrosso, 2016, Proceedings of the National Academy of Sciences.

Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses.

Carlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, 2015, Physical review letters.

One-loop diagrams in the Random Euclidean Matching Problem

Giorgio Parisi, Carlo Lucibello, Gabriele Sicuro, 2016, Physical review. E.

Finite Size Corrections to Disordered Systems : mean field results and applications to finite dimensional models

C. Lucibello, 2015, 1502.02471.

Learning may need only a few bits of synaptic precision.

Carlo Baldassi, Carlo Lucibello, Luca Saglietti, 2016, Physical review. E.

The random fractional matching problem

G. Parisi, C. Lucibello, G. Sicuro, 2018, 1802.02997.

The Statistical Mechanics of Random Set Packing and a Generalization of the Karp-Sipser Algorithm

C. Lucibello, F. Ricci-Tersenghi, 2013, 1311.3254.

Anomalous finite size corrections in random field models

Giorgio Parisi, Carlo Lucibello, Federico Ricci-Tersenghi, 2014, 1406.6577.

Finite-size corrections to disordered systems on Erdös-Rényi random graphs

Giorgio Parisi, Carlo Lucibello, Federico Ricci-Tersenghi, 2013, 1305.3187.

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

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

Efficient coding of facial stimuli in primate inferotemporal cortex

C. Lucibello, G. Pezzulo, Luca Mariani, 2022, 2208.10545.

Finite Size Corrections in Disordered Systems and Optimization Problems

Parisi, C. Lucibello, Federico Ricci-Tersenghi, 2013 .

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.

Clustering of solutions in the symmetric binary perceptron

Riccardo Della Vecchia, R. Zecchina, Carlo Baldassi, 2019, Journal of Statistical Mechanics: Theory and Experiment.

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.

Finite-size corrections to disordered Ising models on random regular graphs.

Tommaso Rizzo, F Ricci-Tersenghi, G. Parisi, 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

One-dimensional disordered Ising models by replica and cavity methods.

F. Morone, C. Lucibello, T. Rizzo, 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

A Scaling Hypothesis for the Euclidean Bipartite Matching Problem

Giorgio Parisi, Carlo Lucibello, Gabriele Sicuro, 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

Neural networks: from the perceptron to deep nets

R. Zecchina, S. Ganguli, C. Lucibello, 2023, 2304.06636.

Reconstruction of pairwise interactions using energy-based models pdf

Carlo Lucibello, Christoph Feinauer, C. Lucibello, 2020, MSML.

Generalized approximate survey propagation for high-dimensional estimation pdf

Carlo Lucibello, Luca Saglietti, Yue M. Lu, 2019, ICML.

Noise-cleaning the precision matrix of fMRI time series

C. Lucibello, T. Gili, Francesca Santucci, 2023, 2302.02951.

On the role of synaptic stochasticity in training low-precision neural networks

Hilbert J. Kappen, Carlo Baldassi, Carlo Lucibello, 2017, Physical review letters.

Information-theoretical analysis of the neural code for decoupled face representation

C. Lucibello, G. Pezzulo, Luca Mariani, 2022, PloS one.

Deep learning via message passing algorithms based on belief propagation

R. Zecchina, C. Lucibello, Fabrizio Pittorino, 2021, Mach. Learn. Sci. Technol..

Critical initialisation in continuous approximations of binary neural networks

C. Lucibello, L. White, I. Fuss, 2019, ICLR.

Interpretable pairwise distillations for generative protein sequence models

C. Lucibello, Barthélémy Meynard-Piganeau, C. Feinauer, 2021, bioRxiv.

Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery

F. Krzakala, L. Zdeborová, C. Lucibello, 2023, Information Theory Workshop.

The Exponential Capacity of Dense Associative Memories

C. Lucibello, Marc M'ezard, 2023, ArXiv.

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

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

Efﬁcient coding of facial stimuli in primate inferotemporal cortex

C. Lucibello, G. Pezzulo, Luca Mariani, 2022 .

Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes

C. Borgs, J. Chayes, R. Zecchina, 2016, Proceedings of the National Academy of Sciences.

Storage and Learning Phase Transitions in the Random-Features Hopfield Model.

C. Lucibello, M. Negri, Gabriele Perugini, 2023, Physical review letters.

The Hidden-Manifold Hopfield Model and a learning phase transition

C. Lucibello, M. Negri, Gabriele Perugini, 2023, ArXiv.