1 citations · 1 across the 10 of their papers we have counts for
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Convergence of a Low-Rank Strang Splitting for Stiff Matrix Differential Equations
Carmen Scalone, Nicola Guglielmi
We propose and analyze a second-order Strang splitting method for a class of stiff matrix differential equations with Sylvester-type structure. The method splits the dynamics into…
Approximation properties of neural ODEs
Arturo De Marinis, Davide Murari, Elena Celledoni +3
We study the approximation properties of neural ordinary differential equations (neural ODEs) in the space of continuous functions. Since a neural ODE requires input and output dim…
Changing the ranking in eigenvector centrality of a weighted graph by small perturbations
Michele Benzi, Nicola Guglielmi
In this article, we consider eigenvector centrality for the nodes of a graph and study the robustness (and stability) of this popular centrality measure. For a given weighted graph…
Improving the robustness of neural ODEs with minimal weight perturbation
Arturo De Marinis, Nicola Guglielmi, Stefano Sicilia +1
We propose a method to enhance the stability of a neural ordinary differential equation (neural ODE) by reducing the maximum error growth subsequent to a perturbation of the initia…
Contractivity of neural ODEs: an eigenvalue optimization problem
Nicola Guglielmi, Arturo De Marinis, Anton Savostianov +1
We propose a novel methodology to solve a key eigenvalue optimization problem which arises in the contractivity analysis of neural ODEs. When looking at contractivity properties of…
Cholesky-like Preconditioner for Hodge Laplacians via Heavy Collapsible Subcomplex
Anton Savostianov, Francesco Tudisco, Nicola Guglielmi
Techniques based on -th order Hodge Laplacian operators are widely used to describe the topology as well as the governing dynamics of high-order systems modeled as simplic…