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08/26/2023
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel
Reduced order models (ROMs) are widely used in scientific computing to t...
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05/31/2023
Reduced order models for the buckling of hyperelastic beams
In this paper, we discuss reduced order modelling approaches to bifurcat...
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05/15/2023
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs
The present work proposes a framework for nonlinear model order reductio...
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10/12/2021
Model order reduction for bifurcating phenomena in Fluid-Structure Interaction problems
This work explores the development and the analysis of an efficient redu...
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09/22/2021
An artificial neural network approach to bifurcating phenomena in computational fluid dynamics
This work deals with the investigation of bifurcating fluid phenomena us...
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10/26/2020
Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier-Stokes equations with model order reduction
This work deals with optimal control problems as a strategy to drive bif...
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12/12/2019
Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method
The majority of the most common physical phenomena can be described usin...
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07/16/2019
