Parsimonious physics-informed random projection neural networks for initial value problems of ODEs and index-1 DAEs von Fabiani, Gianluca, Galaris, Evangelos, Russo, Lucia, Siettos, Constantinos

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Task-oriented machine learning surrogates for tipping points of agent-based models von Fabiani, Gianluca, Evangelou, Nikolaos, Cui, Tianqi, Bello-Rivas, Juan M., Martin-Linares, Cristina P., Siettos, Constantinos, Kevrekidis, Ioannis G.

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Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients von Calabrò, Francesco, Fabiani, Gianluca, Siettos, Constantinos

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Numerical solution and bifurcation analysis of nonlinear partial differential equations with extreme learning machines von Fabiani, Gianluca, Calabrò, Francesco, Russo, Lucia, Siettos, Constantinos

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Numerical Bifurcation Analysis of PDEs From Lattice Boltzmann Model Simulations: a Parsimonious Machine Learning Approach von Galaris, Evangelos, Fabiani, Gianluca, Gallos, Ioannis, Kevrekidis, Ioannis, Siettos, Constantinos

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RandONets: Shallow networks with random projections for learning linear and nonlinear operators von Fabiani, Gianluca, Kevrekidis, Ioannis G., Siettos, Constantinos, Yannacopoulos, Athanasios N.

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Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning von Patsatzis, Dimitrios, Fabiani, Gianluca, Russo, Lucia, Siettos, Constantinos

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Discrete-time nonlinear feedback linearization via physics-informed machine learning von Alvarez, Hector Vargas, Fabiani, Gianluca, Kazantzis, Nikolaos, Siettos, Constantinos, Kevrekidis, Ioannis G.

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Nonlinear discrete-time observers with Physics-Informed Neural Networks von Vargas Alvarez, Hector, Fabiani, Gianluca, Kazantzis, Nikolaos, Kevrekidis, Ioannis G., Siettos, Constantinos

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On the accuracy of interpolation based on single-layer artificial neural networks with a focus on defeating the Runge phenomenon von Auricchio, Ferdinando, Belardo, Maria Roberta, Calabrò, Francesco, Fabiani, Gianluca, Pascaner, Ariel F.

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Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications von Fabiani, Gianluca

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Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications von Fabiani, Gianluca

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Stability Analysis of Physics-Informed Neural Networks for Stiff Linear Differential Equations von Fabiani, Gianluca, Bollt, Erik, Siettos, Constantinos, Yannacopoulos, Athanasios N

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RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators von Fabiani, Gianluca, Kevrekidis, Ioannis G, Siettos, Constantinos, Yannacopoulos, Athanasios N

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Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning von Patsatzis, Dimitrios G, Fabiani, Gianluca, Russo, Lucia, Siettos, Constantinos

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Extreme learning machine collocation for the numerical solution of elliptic PDEs with sharp gradients von Calabrò, Francesco, Fabiani, Gianluca, Siettos, Constantinos

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Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks von Hector Vargas Alvarez, Fabiani, Gianluca, Kevrekidis, Ioannis G, Kazantzis, Nikolaos, Siettos, Constantinos

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Parsimonious Physics-Informed Random Projection Neural Networks for Initial-Value Problems of ODEs and index-1 DAEs von Fabiani, Gianluca, Galaris, Evangelos, Russo, Lucia, Siettos, Constantinos

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Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approach von Galaris, Evangelos, Fabiani, Gianluca, Gallos, Ioannis, Kevrekidis, Ioannis, Siettos, Constantinos

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On the accuracy of interpolation based on single-layer artificial neural networks with a focus on defeating the Runge phenomenon von Auricchio, Ferdinando, Belardo, Maria Roberta, Fabiani, Gianluca, Calabrò, Francesco, Pascaner, Ariel F

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