Carlo Lucibello

According to our database, Carlo Lucibello authored at least 28 papers between 2014 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Benchmarking Graph Neural Networks in Solving Hard Constraint Satisfaction Problems.

Geri Skenderi, Lorenzo Buffoni, Francesco D'Amico, David Machado, Raffaele Marino, Matteo Negri, Federico Ricci-Tersenghi, Carlo Lucibello, Maria Chiara Angelini

CoRR, February, 2026

Emergence of Distortions in High-Dimensional Guided Diffusion Models.

Enrico Ventura, Beatrice Achilli, Luca Ambrogioni, Carlo Lucibello

CoRR, February, 2026

2025

Sampling through Algorithmic Diffusion in non-convex Perceptron problems.

Elizaveta Demyanenko, Davide Straziota, Carlo Baldassi, Carlo Lucibello

CoRR, February, 2025

GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia.

Carlo Lucibello, Aurora Rossi

J. Mach. Learn. Res., 2025

Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms.

Davide Straziota, Elizaveta Demyanenko, Carlo Baldassi, Carlo Lucibello

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Fast Uncovering of Protein Sequence Diversity from Structure.

Luca Alessandro Silva, Barthélémy Meynard-Piganeau, Carlo Lucibello, Christoph Feinauer

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion.

Enrico Ventura, Beatrice Achilli, Gianluigi Silvestri, Carlo Lucibello, Luca Ambrogioni

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Losing dimensions: Geometric memorization in generative diffusion.

Beatrice Achilli, Enrico Ventura, Gianluigi Silvestri, Bao Pham, Gabriel Raya, Dmitry Krotov, Carlo Lucibello, Luca Ambrogioni

CoRR, 2024

The phase diagram of compressed sensing with ℓ₀-norm regularization.

Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová

CoRR, 2024

Random Features Hopfield Networks generalize retrieval to previously unseen examples.

Silvio Kalaj, Clarissa Lauditi, Gabriele Perugini, Carlo Lucibello, Enrico M. Malatesta, Matteo Negri

CoRR, 2024

2023

The star-shaped space of solutions of the spherical negative perceptron.

Brandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello, Enrico M. Malatesta, Gabriele Perugini, Fabrizio Pittorino, Luca Saglietti

CoRR, 2023

The Exponential Capacity of Dense Associative Memories.

Carlo Lucibello, Marc Mézard

CoRR, 2023

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

Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová

CoRR, 2023

The Hidden-Manifold Hopfield Model and a learning phase transition.

Matteo Negri, Clarissa Lauditi, Gabriele Perugini, Carlo Lucibello, Enrico M. Malatesta

CoRR, 2023

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

Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová

Proceedings of the IEEE Information Theory Workshop, 2023

2022

Interpretable pairwise distillations for generative protein sequence models.

Christoph Feinauer, Barthélémy Meynard-Piganeau, Carlo Lucibello

PLoS Comput. Biol., 2022

Deep learning via message passing algorithms based on belief propagation.

Carlo Lucibello, Fabrizio Pittorino, Gabriele Perugini, Riccardo Zecchina

Mach. Learn. Sci. Technol., 2022

2021

Reconstruction of Pairwise Interactions using Energy-Based Models.

Christoph Feinauer, Carlo Lucibello

Proceedings of the Mathematical and Scientific Machine Learning, 2021

Entropic gradient descent algorithms and wide flat minima.

Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Entropic gradient descent algorithms and wide flat minima.

Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Enrico M. Malatesta, Gabriele Perugini, Carlo Baldassi, Matteo Negri, Elizaveta Demyanenko, Riccardo Zecchina

CoRR, 2020

Critical initialisation in continuous approximations of binary neural networks.

George Stamatescu, Federica Gerace, Carlo Lucibello, Ian G. Fuss, Langford B. White

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Signal propagation in continuous approximations of binary neural networks.

George Stamatescu, Federica Gerace, Carlo Lucibello, Ian G. Fuss, Langford B. White

CoRR, 2019

Generalized Approximate Survey Propagation for High-Dimensional Estimation.

Carlo Lucibello, Luca Saglietti, Yue M. Lu

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

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

Carlo Baldassi, Federica Gerace, Hilbert J. Kappen, Carlo Lucibello, Luca Saglietti, Enzo Tartaglione, Riccardo Zecchina

CoRR, 2017

2016

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

Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

Proc. Natl. Acad. Sci. USA, 2016

One-loop diagrams in the Random Euclidean Matching Problem.

Carlo Lucibello, Giorgio Parisi, Gabriele Sicuro

CoRR, 2016

Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles.

Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina

CoRR, 2016

2014

A Scaling Hypothesis for the Euclidean Bipartite Matching Problem.

Sergio Caracciolo, Carlo Lucibello, Giorgio Parisi, Gabriele Sicuro

CoRR, 2014