Deep Learning-based surrogate models for parametrized PDEs: handling
geometric variability through graph neural networks

Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks

3 August 2023

Filippo Tombari

Papers citing "Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks"

18 / 18 papers shown

Title
A Survey on Oversmoothing in Graph Neural Networks T. Konstantin Rusch Michael M. Bronstein Siddhartha Mishra 79 205 0 20 Mar 2023
Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning Shivam Barwey Varun Shankar V. Viswanathan R. Maulik AI4CE 54 22 0 13 Feb 2023
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions Masanobu Horie Naoto Mitsume PINN AI4CE 64 26 0 24 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 87 41 0 16 May 2022
Bayesian operator inference for data-driven reduced-order modeling Mengwu Guo Shane A. McQuarrie Karen E. Willcox 24 35 0 22 Apr 2022
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations N. R. Franco Andrea Manzoni P. Zunino 59 45 0 10 Mar 2021
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition S. Fresca Andrea Manzoni AI4CE 56 214 0 28 Jan 2021
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 77 783 0 07 Oct 2020
Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification Yunsheng Shi Zhengjie Huang Shikun Feng Hui Zhong Wenjin Wang Yu Sun AI4CE 73 782 0 08 Sep 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 131 1,088 0 21 Feb 2020
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs S. Fresca Luca Dede' Andrea Manzoni AI4CE 56 262 0 12 Jan 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 220 2,119 0 08 Oct 2019
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 739 3,119 0 04 Jun 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 454 20,124 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 470 15,218 0 07 Jun 2017
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 524 1,408 0 01 Dec 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 595 28,999 0 09 Sep 2016
Learning Convolutional Neural Networks for Graphs Mathias Niepert Mohamed Ahmed Konstantin Kutzkov GNN SSL 135 2,154 0 17 May 2016

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