Non intrusive reduced order modeling of parametrized PDEs by kernel POD and neural networks

A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs

(2021) Stefania Fresca et al.   JOURNAL OF SCIENTIFIC COMPUTING

Deep learning-based reduced order models in cardiac electrophysiology

(2020) Stefania Fresca et al.   PLoS One

Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

(2019) Qian Wang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine learning for fast and reliable solution of time-dependent differential equations

(2019) F. Regazzoni et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

(2019) Kookjin Lee et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Neural network closures for nonlinear model order reduction

(2018) Omer San et al.   ADVANCES IN COMPUTATIONAL MATHEMATICS

Numerical approximation of parametrized problems in cardiac electrophysiology by a local reduced basis method

(2018) Stefano Pagani et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Reduced order modeling for nonlinear structural analysis using Gaussian process regression

(2018) Mengwu Guo et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Non-intrusive reduced order modeling of nonlinear problems using neural networks

(2018) J.S. Hesthaven et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Data-driven reduced order modeling for time-dependent problems

(2018) Mengwu Guo et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Manifold learning for the emulation of spatial fields from computational models

(2016) W.W. Xing et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Isogeometric Analysis and error estimates for high order partial differential equations in fluid dynamics

(2014) Anna Tagliabue et al.   COMPUTERS & FLUIDS

Reduced dimensional Gaussian process emulators of parametrized partial differential equations based on Isomap

(2014) W. Xing et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES