Non-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method

1 March 2022

Papers citing "Non-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method"

7 / 7 papers shown

Title
A practical existence theorem for reduced order models based on convolutional autoencoders N. R. Franco Simone Brugiapaglia AI4CE 83 4 0 01 Feb 2024
Generative Adversarial Reduced Order Modelling Dario Coscia N. Demo G. Rozza GAN AI4CE 160 7 0 25 May 2023
Hyper-Reduced Autoencoders for Efficient and Accurate Nonlinear Model Reductions Jorio Cocola John Tencer F. Rizzi E. Parish P. Blonigan 23 5 0 16 Mar 2023
A two stages Deep Learning Architecture for Model Reduction of Parametric Time-Dependent Problems Isabella Carla Gonnella M. Hess G. Stabile G. Rozza AI4CE 80 2 0 24 Jan 2023
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation A. Ivagnes N. Demo G. Rozza MedIm AI4CE 61 8 0 26 Oct 2022
A Continuous Convolutional Trainable Filter for Modelling Unstructured Data Dario Coscia L. Meneghetti N. Demo G. Stabile G. Rozza 82 8 0 24 Oct 2022
Neural Galerkin Schemes with Active Learning for High-Dimensional Evolution Equations Joan Bruna Benjamin Peherstorfer Eric Vanden-Eijnden 103 69 0 02 Mar 2022