Data-driven Nonlinear Parametric Model Order Reduction Framework using
Deep Hierarchical Variational Autoencoder

Data-driven Nonlinear Parametric Model Order Reduction Framework using Deep Hierarchical Variational Autoencoder

10 July 2023

Papers citing "Data-driven Nonlinear Parametric Model Order Reduction Framework using Deep Hierarchical Variational Autoencoder"

9 / 9 papers shown

Title
$β$ -Variational autoencoders and transformers for reduced-order modelling of fluid flows Alberto Solera-Rico Carlos Sanmiguel Vila Miguel Gómez-López Yuning Wang Abdulrahman Almashjary Scott T. M. Dawson Ricardo Vinuesa DRL 38 78 0 07 Apr 2023
Physics-aware Reduced-order Modeling of Transonic Flow via $β$ -Variational Autoencoder Yu-Eop Kang Sunwoong Yang K. Yee DRL AI4CE 43 25 0 02 May 2022
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Hamidreza Eivazi S. L. C. Martínez S. Hoyas Ricardo Vinuesa 56 92 0 03 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 51 61 0 23 Jul 2021
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder Youngkyu Kim Youngsoo Choi David Widemann T. Zohdi AI4CE 32 191 0 25 Sep 2020
Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function Stephen G. Odaibo GAN BDL DRL 20 54 0 21 Jul 2019
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing Hao Fu Chunyuan Li Xiaodong Liu Jianfeng Gao Asli Celikyilmaz Lawrence Carin ODL 63 362 0 25 Mar 2019
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 196 5,502 0 23 Nov 2015
Generating Sentences from a Continuous Space Samuel R. Bowman Luke Vilnis Oriol Vinyals Andrew M. Dai Rafal Jozefowicz Samy Bengio DRL 74 2,352 0 19 Nov 2015