A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs

12 January 2020

Papers citing "A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs"

22 / 72 papers shown

Title
Assessment of convolutional recurrent autoencoder network for learning wave propagation Wrik Mallik R. Jaiman J. Jelovica BDL 6 1 0 12 Apr 2022
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes C. Heaney Zef Wolffs Jón Atli Tómasson L. Kahouadji P. Salinas A. Nicolle Omar K. Matar Ionel M. Navon N. Srinil Christopher C. Pain AI4CE 29 21 0 13 Feb 2022
Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning T. Kadeethum F. Ballarin Daniel O’Malley Youngsoo Choi N. Bouklas H. Yoon AI4CE 16 17 0 11 Feb 2022
Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs Ludovica Cicci S. Fresca Andrea Manzoni AI4CE 12 25 0 05 Feb 2022
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models Federico Fatone S. Fresca Andrea Manzoni AI4TS 20 16 0 25 Jan 2022
Predicting waves in fluids with deep neural network Indu Kant Deo R. Jaiman AI4Cl 14 24 0 17 Jan 2022
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs Guang Lin Christian Moya Zecheng Zhang 15 30 0 03 Nov 2021
A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling A. Gruber M. Gunzburger L. Ju Zhu Wang GNN 32 62 0 05 Oct 2021
An artificial neural network approach to bifurcating phenomena in computational fluid dynamics F. Pichi F. Ballarin G. Rozza J. Hesthaven AI4CE 18 71 0 22 Sep 2021
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques T. Kadeethum F. Ballarin Y. Cho Daniel O’Malley H. Yoon N. Bouklas AI4CE 8 61 0 23 Jul 2021
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations Pranshu Pant Ruchi Doshi Pranav Bahl A. Farimani AI4CE 15 80 0 09 Jul 2021
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models S. Fresca Andrea Manzoni AI4CE 11 36 0 10 Jun 2021
Data Assimilation Predictive GAN (DA-PredGAN): applied to determine the spread of COVID-19 Vinicius L. S. Silva C. Heaney Yaqi Li Christopher C. Pain AI4CE 16 23 0 17 May 2021
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations N. R. Franco Andrea Manzoni P. Zunino 18 45 0 10 Mar 2021
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities Mengwu Guo Andrea Manzoni Maurice Amendt Paolo Conti J. Hesthaven 70 95 0 26 Feb 2021
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition S. Fresca Andrea Manzoni AI4CE 16 212 0 28 Jan 2021
Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification L. Scarabosio 8 9 0 18 Jan 2021
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems Kookjin Lee E. Parish 6 65 0 28 Oct 2020
A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations John Tencer Kevin Potter AI4CE 15 13 0 11 Jun 2020
Deep learning-based reduced order models in cardiac electrophysiology S. Fresca Andrea Manzoni Luca Dede' A. Quarteroni 8 66 0 02 Jun 2020
Model Reduction and Neural Networks for Parametric PDEs K. Bhattacharya Bamdad Hosseini Nikola B. Kovachki Andrew M. Stuart 11 317 0 07 May 2020
Lip Reading Sentences in the Wild Joon Son Chung A. Senior Oriol Vinyals Andrew Zisserman 162 784 0 16 Nov 2016