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International Journal for Numerical Methods in Biomedical Engineering
|
February 18, 2021
Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning
Stefano Pagani, Andrea Manzoni
International Journal for Numerical Methods in Biomedical Engineering
|
November 4, 2014
Model reduction techniques for fast blood flow simulation in parametrized geometries
Andrea Manzoni, Alfio Quarteroni, Gianluigi Rozza
Plos One
|
May 21, 2024
Uncertainty quantification and sensitivity analysis of neuron models with ion concentration dynamics
Letizia Signorelli, Andrea Manzoni, Marte J Sætra
Neural Networks : the Official Journal of the International Neural Network Society
|
January 28, 2025
On latent dynamics learning in nonlinear reduced order modeling
Nicola Farenga, Stefania Fresca, Simone Brivio, et al.
Frontiers in Physiology
|
October 11, 2021
POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium
Stefania Fresca, Andrea Manzoni, Luca Dedè, et al.
Sensors (Basel, Switzerland)
|
July 2, 2021
An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics
Luca Rosafalco, Andrea Manzoni, Stefano Mariani, et al.
International Journal for Numerical Methods in Biomedical Engineering
|
June 27, 2013
A reduced computational and geometrical framework for inverse problems in hemodynamics
Toni Lassila, Andrea Manzoni, Alfio Quarteroni, et al.
Sensors (Basel, Switzerland)
|
March 30, 2023
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, et al.
Plos One
|
October 1, 2020
Deep learning-based reduced order models in cardiac electrophysiology
Stefania Fresca, Andrea Manzoni, Luca Dedè, et al.
Pacing and Clinical Electrophysiology : PACE
|
February 17, 2021
Data integration for the numerical simulation of cardiac electrophysiology
Stefano Pagani, Luca Dede', Andrea Manzoni, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 29) with videos related to
Sort By:
Page
of 3
International Journal for Numerical Methods in Biomedical Engineering
|
February 18, 2021
Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning
Stefano Pagani, Andrea Manzoni
International Journal for Numerical Methods in Biomedical Engineering
|
November 4, 2014
Model reduction techniques for fast blood flow simulation in parametrized geometries
Andrea Manzoni, Alfio Quarteroni, Gianluigi Rozza
Plos One
|
May 21, 2024
Uncertainty quantification and sensitivity analysis of neuron models with ion concentration dynamics
Letizia Signorelli, Andrea Manzoni, Marte J Sætra
Neural Networks : the Official Journal of the International Neural Network Society
|
January 28, 2025
On latent dynamics learning in nonlinear reduced order modeling
Nicola Farenga, Stefania Fresca, Simone Brivio, et al.
Frontiers in Physiology
|
October 11, 2021
POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium
Stefania Fresca, Andrea Manzoni, Luca Dedè, et al.
Sensors (Basel, Switzerland)
|
July 2, 2021
An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics
Luca Rosafalco, Andrea Manzoni, Stefano Mariani, et al.
International Journal for Numerical Methods in Biomedical Engineering
|
June 27, 2013
A reduced computational and geometrical framework for inverse problems in hemodynamics
Toni Lassila, Andrea Manzoni, Alfio Quarteroni, et al.
Sensors (Basel, Switzerland)
|
March 30, 2023
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches
Giorgio Gobat, Stefania Fresca, Andrea Manzoni, et al.
Plos One
|
October 1, 2020
Deep learning-based reduced order models in cardiac electrophysiology
Stefania Fresca, Andrea Manzoni, Luca Dedè, et al.
Pacing and Clinical Electrophysiology : PACE
|
February 17, 2021
Data integration for the numerical simulation of cardiac electrophysiology
Stefano Pagani, Luca Dede', Andrea Manzoni, et al.
Page
of 3