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SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability

27 April 2022

Papers citing "SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability"

25 / 25 papers shown

Title
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 197 6 0 10 Feb 2023
MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling Lu Zhang Huaiqian You Yue Yu OffRL 80 7 0 04 Jun 2022
Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport Lu Lu R. Pestourie Steven G. Johnson Giuseppe Romano AI4CE 73 108 0 14 Apr 2022
Learning two-phase microstructure evolution using neural operators and autoencoder architectures Vivek Oommen K. Shukla S. Goswami Rémi Dingreville George Karniadakis AI4CE 105 124 0 11 Apr 2022
MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems Jiahao Zhang Shiqi Zhang Guang Lin 95 15 0 07 Apr 2022
Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling Huaiqian You Quinn Zhang Colton J. Ross Chung-Hao Lee Yue Yu AI4CE 95 107 0 15 Mar 2022
Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions Lesley Tan Liang Chen 57 14 0 17 Feb 2022
MIONet: Learning multiple-input operators via tensor product Pengzhan Jin Shuai Meng Lu Lu 93 174 0 12 Feb 2022
Learning Operators with Coupled Attention Georgios Kissas Jacob H. Seidman Leonardo Ferreira Guilhoto V. Preciado George J. Pappas P. Perdikaris 81 113 0 04 Jan 2022
Machine-learning custom-made basis functions for partial differential equations B. Meuris S. Qadeer P. Stinis 32 3 0 09 Nov 2021
Improved architectures and training algorithms for deep operator networks Sizhuang He Hanwen Wang P. Perdikaris AI4CE 104 107 0 04 Oct 2021
Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network Minglang Yin Ehsan Ban B. Rego Enrui Zhang C. Cavinato J. Humphrey George Karniadakis AI4CE 85 54 0 25 Aug 2021
Neural Operator: Learning Maps Between Function Spaces Nikola B. Kovachki Zong-Yi Li Burigede Liu Kamyar Azizzadenesheli K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 138 453 0 19 Aug 2021
A physics-informed variational DeepONet for predicting the crack path in brittle materials S. Goswami Minglang Yin Yue Yu G. Karniadakis AI4CE 58 196 0 16 Aug 2021
The Neural Network shifted-Proper Orthogonal Decomposition: a Machine Learning Approach for Non-linear Reduction of Hyperbolic Equations Davide Papapicco N. Demo M. Girfoglio G. Stabile G. Rozza 37 55 0 14 Aug 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 102 710 0 19 Mar 2021
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems Craig Gin D. Shea Steven L. Brunton J. Nathan Kutz 74 90 0 31 Dec 2020
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 509 2,453 0 18 Oct 2020
A physics-informed operator regression framework for extracting data-driven continuum models Ravi G. Patel N. Trask M. Wood E. Cyr AI4CE 83 105 0 25 Sep 2020
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder Youngkyu Kim Youngsoo Choi David Widemann T. Zohdi AI4CE 59 200 0 25 Sep 2020
Physics-aware registration based auto-encoder for convection dominated PDEs R. Mojgani Maciej Balajewicz DiffM AI4CE 67 25 0 28 Jun 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 208 749 0 07 Mar 2020
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems E. Qian Boris Kramer Benjamin Peherstorfer Karen E. Willcox AI4CE 91 267 0 17 Dec 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,158 0 08 Oct 2019
Machine Learning for Fluid Mechanics Steven Brunton B. R. Noack Petros Koumoutsakos AI4CE PINN 91 2,128 0 27 May 2019