Gianluca Fabiani

22 papers Journal 22
YearRankTypeTitle / Venue / Authors
2026 J jnl
Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach.
CoRR
Gianluca Fabiani, Michail E. Kavousanakis, Constantinos I. Siettos, Ioannis G. Kevrekidis
2025 J jnl
Enabling Local Neural Operators to perform Equation-Free System-Level Analysis.
CoRR
Gianluca Fabiani, Hannes Vandecasteele, Somdatta Goswami, Constantinos I. Siettos, Ioannis G. Kevrekidis
2025 J jnl
Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators.
CoRR
Gianluca Fabiani, Constantinos I. Siettos, Ioannis G. Kevrekidis
2025 J jnl
HEATNETs: Explainable Random Feature Neural Networks for High-Dimensional Parabolic PDEs.
CoRR
Kyriakos Georgiou, Gianluca Fabiani, Constantinos I. Siettos, Athanasios N. Yannacopoulos
2025 J jnl
RandONets: Shallow networks with random projections for learning linear and nonlinear operators.
J. Comput. Phys.
Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos I. Siettos, Athanasios N. Yannacopoulos
2025 J jnl
Random Projection Neural Networks of Best Approximation: Convergence Theory and Practical Applications.
SIAM J. Math. Data Sci.
Gianluca Fabiani
2024 J jnl
Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks.
CoRR
Hector Vargas Alvarez, Gianluca Fabiani, Ioannis G. Kevrekidis, Nikolaos Kazantzis, Constantinos I. Siettos
2024 J jnl
On the accuracy of interpolation based on single-layer artificial neural networks with a focus on defeating the Runge phenomenon.
Soft Comput.
Ferdinando Auricchio, Maria Roberta Belardo, Francesco Calabrò, Gianluca Fabiani, Ariel F. Pascaner
2024 J jnl
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators.
CoRR
Gianluca Fabiani, Ioannis G. Kevrekidis, Constantinos I. Siettos, Athanasios N. Yannacopoulos
2024 J jnl
Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications.
CoRR
Gianluca Fabiani
2024 J jnl
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning.
SIAM J. Sci. Comput.
Dimitrios G. Patsatzis, Gianluca Fabiani, Lucia Russo, Constantinos I. Siettos
2024 J jnl
Stability Analysis of Physics-Informed Neural Networks for Stiff Linear Differential Equations.
CoRR
Gianluca Fabiani, Erik Bollt, Constantinos I. Siettos, Athanasios N. Yannacopoulos
2023 J jnl
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning.
CoRR
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos I. Siettos, Ioannis G. Kevrekidis
2023 J jnl
Discrete-time nonlinear feedback linearization via physics-informed machine learning.
J. Comput. Phys.
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos I. Siettos, Ioannis G. Kevrekidis
2023 J jnl
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning.
CoRR
Dimitrios G. Patsatzis, Gianluca Fabiani, Lucia Russo, Constantinos I. Siettos
2023 J jnl
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points.
CoRR
Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas, Cristina P. Martin-Linares, Constantinos I. Siettos, Ioannis G. Kevrekidis
2022 J jnl
Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach.
CoRR
Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos, Ioannis G. Kevrekidis, Constantinos I. Siettos
2022 J jnl
Numerical Bifurcation Analysis of PDEs From Lattice Boltzmann Model Simulations: a Parsimonious Machine Learning Approach.
J. Sci. Comput.
Evangelos Galaris, Gianluca Fabiani, Ioannis Gallos, Ioannis G. Kevrekidis, Constantinos I. Siettos
2022 J jnl
Parsimonious Physics-Informed Random Projection Neural Networks for Initial-Value Problems of ODEs and index-1 DAEs.
CoRR
Gianluca Fabiani, Evangelos Galaris, Lucia Russo, Constantinos I. Siettos
2021 J jnl
Numerical Solution and Bifurcation Analysis of Nonlinear Partial Differential Equations with Extreme Learning Machines.
CoRR
Gianluca Fabiani, Francesco Calabrò, Lucia Russo, Constantinos I. Siettos
2021 J jnl
Numerical solution and bifurcation analysis of nonlinear partial differential equations with extreme learning machines.
J. Sci. Comput.
Gianluca Fabiani, Francesco Calabrò, Lucia Russo, Constantinos I. Siettos
2020 J jnl
Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients.
CoRR
Francesco Calabrò, Gianluca Fabiani, Constantinos I. Siettos