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From the 1 of 11 linked papers with an AI index.

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20242026
most citedA short review on the maximum clique problem algorithms with classical, AI, and quantum methods

1 citations · 1 across the 3 of their papers we have counts for

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11 papers

cs.AI20261 cited

A short review on the maximum clique problem algorithms with classical, AI, and quantum methods

Raffaele Marino, Lorenzo Buffoni, Bogdan Zavalnij

The paper surveys algorithms for solving the maximum clique problem, covering classical exact and heuristic methods as well as recent graph neural network and quantum computing app…

cond-mat.dis-nn2026

Approximating velocity fields with planted attractors via Neural-ODEs for classification purposes

Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni +3

In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks. The planted attractors serve as indicat…

quant-ph2026

Quantum work statistics and coherence effects in quenched bosonic Josephson junctions

Mattia Orlandini, Stefano Gherardini, Lorenzo Buffoni +1

We investigate the non-equilibrium work statistics originating from a sudden quench in a bosonic Josephson junction. In particular, by employing the Holstein-Primakoff approximatio…

quant-ph2026

Squeezing and adiabaticity breaking in time-dependent quantum harmonic oscillators

Mattia Orlandini, Beatrice Donelli, Lorenzo Buffoni +1

The quantum harmonic oscillator with time-dependent frequency is a paradigmatic model of driven quantum dynamics and one of the few nontrivial systems that admits an exact analytic…

cond-mat.dis-nn2026

Exact Fixed-Point Constraints in Neural-ODEs with Provable Universality

Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni +3

We introduce a technique that enables Neural-ODEs to approximate arbitrary velocity fields with a priori planted fixed-points. Specifically, a recipe is given to explicitly accommo…

cond-mat.stat-mech2026

Smart Walkers in Discrete Space

Gianluca Peri, Lorenzo Buffoni, Giacomo Chiti +4

We study the statistical properties of trainable agents moving in discrete space. After introducing the mathematical framework, we first analyze the dynamics of two completely rand…