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RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators

RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators

Gianluca Fabiani
Ioannis G. Kevrekidis
Constantinos Siettos
A. Yannacopoulos
ArXiv (abs)PDFHTML

Papers citing "RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators"

6 / 6 papers shown
Title
Rapid training of Hamiltonian graph networks without gradient descent
Rapid training of Hamiltonian graph networks without gradient descent
Atamert Rahma
Chinmay Datar
Ana Cukarska
Felix Dietrich
AI4CE
29
0
0
06 Jun 2025
Enabling Local Neural Operators to perform Equation-Free System-Level Analysis
Enabling Local Neural Operators to perform Equation-Free System-Level Analysis
Gianluca Fabiani
H. Vandecasteele
S. Goswami
Constantinos Siettos
Ioannis G. Kevrekidis
455
1
0
05 May 2025
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
Dimitrios G. Patsatzis
Mario di Bernardo
L. Russo
Constantinos Siettos
AI4CE
50
2
0
29 Oct 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
Madison Cooley
Varun Shankar
Robert M. Kirby
Shandian Zhe
110
2
0
04 Oct 2024
Stability Analysis of Physics-Informed Neural Networks for Stiff Linear Differential Equations
Stability Analysis of Physics-Informed Neural Networks for Stiff Linear Differential Equations
Gianluca Fabiani
Erik Bollt
Constantinos Siettos
A. Yannacopoulos
67
1
0
27 Aug 2024
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology
Mario De Florio
Zongren Zou
Daniele E. Schiavazzi
George Karniadakis
56
4
0
13 Aug 2024

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