MIONet: Learning multiple-input operators via tensor product

12 February 2022

Papers citing "MIONet: Learning multiple-input operators via tensor product"

27 / 27 papers shown

Title
Spatiotemporal Field Generation Based on Hybrid Mamba-Transformer with Physics-informed Fine-tuning Peimian Du Jiabin Liu Xiaowei Jin Mengwang Zuo Hui Li AI4CE 110 0 0 16 May 2025
Ensemble and Mixture-of-Experts DeepONets For Operator Learning Ramansh Sharma Varun Shankar 101 0 0 20 May 2024
Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation Jingmin Sun Yuxuan Liu Zecheng Zhang Hayden Schaeffer AI4CE 106 20 0 18 Apr 2024
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks Mitchell Daneker Zhen Zhang George Karniadakis Lu Lu CML 42 36 0 03 Feb 2022
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network Huaiqian You Yue Yu M. DÉlia T. Gao Stewart Silling 82 74 0 06 Jan 2022
Learning Operators with Coupled Attention Georgios Kissas Jacob H. Seidman Leonardo Ferreira Guilhoto V. Preciado George J. Pappas P. Perdikaris 77 113 0 04 Jan 2022
Exponential Convergence of Deep Operator Networks for Elliptic Partial Differential Equations C. Marcati Christoph Schwab 72 39 0 15 Dec 2021
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs Guang Lin Christian Moya Zecheng Zhang 42 30 0 03 Nov 2021
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 84 468 0 01 Nov 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 81 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 117 453 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 54 195 0 16 Aug 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 97 707 0 19 Mar 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 97 520 0 09 Feb 2021
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 500 2,444 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 76 104 0 25 Sep 2020
The Random Feature Model for Input-Output Maps between Banach Spaces Nicholas H. Nelsen Andrew M. Stuart 79 144 0 20 May 2020
Model Reduction and Neural Networks for Parametric PDEs K. Bhattacharya Bamdad Hosseini Nikola B. Kovachki Andrew M. Stuart 220 332 0 07 May 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 202 748 0 07 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,150 0 08 Oct 2019
GMLS-Nets: A framework for learning from unstructured data Nathaniel Trask Ravi G. Patel B. Gross P. Atzberger 36 42 0 07 Sep 2019
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 99 1,538 0 10 Jul 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 123 373 0 13 May 2019
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 111 409 0 21 Sep 2018
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 123 1,389 0 30 Sep 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 91 2,066 0 24 Aug 2017
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014