Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling Curves

24 November 2020

Papers citing "Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling Curves"

7 / 7 papers shown

Title
Machine learning for modelling unstructured grid data in computational physics: a review Sibo Cheng Marc Bocquet Weiping Ding Tobias S. Finn Rui Fu ... Yong Zeng Mingrui Zhang Hao Zhou Kewei Zhu Rossella Arcucci PINN AI4CE 114 0 0 13 Feb 2025
Using AI libraries for Incompressible Computational Fluid Dynamics Boyang Chen C. Heaney Christopher C. Pain AI4CE 24 4 0 27 Feb 2024
Adaptive learning of effective dynamics: Adaptive real-time, online modeling for complex systems Ivica Kicic Pantelis R. Vlachas G. Arampatzis Michail Chatzimanolakis Leonidas J. Guibas P. Koumoutsakos AI4CE 22 6 0 04 Apr 2023
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models Sibo Cheng Jianhua Chen Charitos Anastasiou P. Angeli Omar K. Matar Yi-Ke Guo Christopher C. Pain Rossella Arcucci AI4CE 36 60 0 07 Apr 2022
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
Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation Julian Mack Rossella Arcucci Miguel Molina-Solana Yi-Ke Guo 3DPC 48 34 0 06 Jan 2021
An autoencoder-based reduced-order model for eigenvalue problems with application to neutron diffusion Toby R. F. Phillips C. Heaney Paul N. Smith Christopher C. Pain 31 57 0 15 Aug 2020