activity
20142026
most citedA Bayesian Approach to the Naming Game Model

18 citations · 67 across the 17 of their papers we have counts for

collaborators

17 papers

cond-mat.stat-mech2026

Beyond Explained Variance: A Cautionary Tale of PCA

Gionni Marchetti

We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via two-dimensional scatterplots,…

cond-mat.stat-mech2026

Learning the Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou Trajectories: A Nonlinear Approach using a Deep Autoencoder Model

Gionni Marchetti

We address the intrinsic dimensionality (ID) of high-dimensional trajectories, comprising data points, of the Fermi-Pasta-Ulam-Tsingou (FPUT) model with $N…

physics.soc-ph2025

Metric Similarity and Manifold Learning of Circular Dichroism Spectra of Proteins

Gionni Marchetti

We present a machine learning analysis of circular dichroism spectra of globular proteins from the SP175 database, using the optimal transport-based -Wasserstein distance $\math…

cond-mat.stat-mech2025★ 4 cited

A Machine Learning Tool to Analyse Spectroscopic Changes in High-Dimensional Data

Alberto Martinez-Serra, Gionni Marchetti, Francesco D'Amico +4

When nanoparticles (NPs) are introduced into a biological solution, layers of biomolecules form on their surface, creating a corona. Understanding how the structure of the protein…

cs.LG2024★ 1 cited

Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou High-Dimensional Trajectories Through Manifold Learning: A Linear Approach

Gionni Marchetti

A data-driven approach based on unsupervised machine learning is proposed to infer the intrinsic dimension of the high-dimensional trajectories of the Fermi-Pasta-Ulam-T…

physics.soc-ph2024★ 1 cited

Generalized Naming Game and Bayesian Naming Game as Dynamical Systems

Gionni Marchetti

We study the -model (-NG) and the Bayesian Naming Game (BNG) as dynamical systems. By applying linear stability analysis to the dynamical system associated with the -model…

cond-mat.mtrl-sci2023★ 2 cited

Revisiting the Thomas-Fermi Potential for Three-Dimensional Condensed Matter Systems

Gionni Marchetti

We proposed a formally exact, probabilistic method to assess the validity of the Thomas-Fermi potential for three-dimensional condensed matter systems where electron dynamics is co…

cond-mat.mtrl-sci2023

Electron-electron Scattering in the Diffusive Regime and Dyakonov-Perel Theory: a case study of spin decoherence in n-type GaAs

Gionni Marchetti

We argue that in the ensemble Monte Carlo approach, the spin decoherence caused by electron-electron interactions in n-type bulk GaAs at room temperature, according to Dyakonov-Per…

physics.comp-ph2021★ 4 cited

Machine Learning S-Wave Scattering Phase Shifts Bypassing the Radial Schrödinger Equation

Alessandro Romualdi, Gionni Marchetti

We present a proof of concept machine learning model resting on a convolutional neural network capable to yield accurate scattering s-wave phase shifts caused by different three-di…

physics.soc-ph2021★ 4 cited

The Role of bilinguals in the Bayesian naming game

Gionni Marchetti, Marco Patriarca, Els Heinsalu

We study the recently introduced Bayesian naming game model, in which the one-shot learning of the minimal naming game is replaced by a more realistic learning process defined acco…

physics.soc-ph2020★ 10 cited

A Bird's-Eye View of Naming Game Dynamics: From Trait Competition to Bayesian Inference

Gionni Marchetti, Els Heinsalu, Marco Patriarca

The present contribution reviews a set of different versions of the basic naming game model, differing in the underlying topology or in the mechanisms regulating the interactions b…

physics.soc-ph2019★ 18 cited

A Bayesian Approach to the Naming Game Model

Gionni Marchetti, Marco Patriarca, Els Heinsalu

We present a novel Bayesian approach to semiotic dynamics, which is a cognitive analogue of the naming game model restricted to two conventions. The one-shot learning that characte…

cond-mat.mtrl-sci2018★ 2 cited

Single-particle Relaxation Time in Doped Semiconductors beyond the Born Approximation

Gionni Marchetti

We compare the magnitudes of the single-particle relaxation time accurately computed by the variable phase approach are with those computed in the first Born approximation for dope…

cond-mat.mes-hall2018★ 4 cited

Inconsistency between Linearized Thomas-Fermi Approximation and Electron-Ionized Impurity Scattering Rate in the first Born Approximation

Gionni Marchetti

We show that by computing the electron-impurity scattering rate at the first order via Fermi's golden rule, and assuming that the localized impurity potential is of Yukawa form, on…

cond-mat.mtrl-sci2016★ 12 cited

Spin Relaxation in GaAs: Importance of Electron-Electron Interactions

Gionni Marchetti, Matthew Hodgson, James McHugh +2

We study spin relaxation in n-type bulk GaAs, due to the Dyakonov--Perel mechanism, using ensemble Monte Carlo methods. Our results confirm that spin relaxation time increases with…

cond-mat.mtrl-sci2016★ 2 cited

Effect of Ionized Impurity Screening on Spin Decoherence at Low and Intermediate Temperatures in GaAs

Gionni Marchetti, Irene D'Amico

We study the effect of charged impurity screening on spin decoherence in bulk {\it n}-type GaAs, and analyse in details the effect of the use of different Born approximations appli…

cond-mat.mtrl-sci2014★ 3 cited

Spin decoherence in n-type GaAs: the effectiveness of the third-body rejection method for electron-electron scattering

Gionni Marchetti, Matthew Hodgson, Irene D'Amico

We study the spin decoherence in n-type bulk GaAs for moderate electronic densities at room temperature using Ensemble Monte Carlo method. We demonstrate that the third-body reject…