The Backtracking Survey Propagation Algorithm for Solving Random K-SAT Problems. - Raffaele Marino; Giorgio Parisi; Federico Ricci-Tersenghi (CoRR, 2015)

Revisiting the Challenges of MaxClique. - Raffaele Marino; Scott Kirkpatrick (CoRR, 2018)

Large independent sets on random d-regular graphs with d small. - Raffaele Marino; Scott Kirkpatrick (CoRR, 2020)

Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization. - Masoud Mohseni; Daniel Eppens; Johan Strümpfer; Raffaele Marino; Vasil S. Denchev; Alan K. Ho; Sergei V. Isakov; Sergio Boixo; Federico Ricci-Tersenghi; Hartmut Neven (CoRR, 2021)

Learning from survey propagation: a neural network for MAX-E-3-SAT. - Raffaele Marino (Mach. Learn. Sci. Technol., 2021)

Hard Optimization Problems have Soft Edges. - Raffaele Marino; Scott Kirkpatrick (CoRR, 2022)

Phase transitions in the mini-batch size for sparse and dense neural networks. - Raffaele Marino; Federico Ricci-Tersenghi (CoRR, 2023)

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)

Where do hard problems really exist? - Raffaele Marino (CoRR, 2023)

A Bridge between Dynamical Systems and Machine Learning: Engineered Ordinary Differential Equations as Classification Algorithm (EODECA). - Raffaele Marino; Lorenzo Giambagli; Lorenzo Chicchi; Lorenzo Buffoni; Duccio Fanelli (CoRR, 2023)

Complex Recurrent Spectral Network. - Lorenzo Chicchi; Lorenzo Giambagli; Lorenzo Buffoni; Raffaele Marino; Duccio Fanelli (CoRR, 2023)

Solving Non-linear Kolmogorov Equations in Large Dimensions by Using Deep Learning: A Numerical Comparison of Discretization Schemes. - Raffaele Marino; Nicolas Macris (J. Sci. Comput., 2023)

Large Independent Sets on Random d-Regular Graphs with Fixed Degree d. - Raffaele Marino; Scott Kirkpatrick (Comput., 2023)

The Garden of Forking Paths: Observing Dynamic Parameters Distribution in Large Language Models. - Carlo Nicolini; Jacopo Staiano; Bruno Lepri; Raffaele Marino (CoRR, 2024)

A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms. - Raffaele Marino; Lorenzo Buffoni; Bogdán Zaválnij (CoRR, 2024)

Automatic Input Feature Relevance via Spectral Neural Networks. - Lorenzo Chicchi; Lorenzo Buffoni; Diego Febbe; Lorenzo Giambagli; Raffaele Marino; Duccio Fanelli (CoRR, 2024)

Fast Analysis of the OpenAI O1-Preview Model in Solving Random K-SAT Problem: Does the LLM Solve the Problem Itself or Call an External SAT Solver? - Raffaele Marino (CoRR, 2024)

Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise. - Lorenzo Chicchi; Duccio Fanelli; Diego Febbe; Lorenzo Buffoni; Francesca Di Patti; Lorenzo Giambagli; Raffaele Marino (CoRR, 2024)

Stable attractors for neural networks classification via ordinary differential equations (SA-nODE). - Raffaele Marino; Lorenzo Buffoni; Lorenzo Chicchi; Lorenzo Giambagli; Duccio Fanelli (Mach. Learn. Sci. Technol., 2024)

Phase transitions in the mini-batch size for sparse and dense two-layer neural networks. - Raffaele Marino; Federico Ricci-Tersenghi (Mach. Learn. Sci. Technol., 2024)

Learning in Wilson-Cowan Model for Metapopulation. - Raffaele Marino; Lorenzo Buffoni; Lorenzo Chicchi; Francesca Di Patti; Diego Febbe; Lorenzo Giambagli; Duccio Fanelli (Neural Comput., 2025)

Daydreaming Hopfield Networks and their surprising effectiveness on correlated data. - Ludovica Serricchio; Dario Bocchi; Claudio Chilin; Raffaele Marino; Matteo Negri; Chiara Cammarota; Federico Ricci-Tersenghi (Neural Networks, 2025)