Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets

19 March 2021

Papers citing "Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets"

50 / 316 papers shown

Title
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition Xinquan Huang Wenlei Shi Qi Meng Yue Wang Xiaotian Gao Jia Zhang Tie-Yan Liu AI4CE 21 8 0 20 Feb 2023
The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach Yongcun Song Xiaoming Yuan Hangrui Yue PINN 27 6 0 16 Feb 2023
Magnetohydrodynamics with Physics Informed Neural Operators S. Rosofsky Eliu A. Huerta AI4CE 15 10 0 13 Feb 2023
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 44 4 0 10 Feb 2023
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains Ali Harandi Ahmad Moeineddin Michael Kaliske Stefanie Reese Shahed Rezaei AI4CE PINN 18 42 0 09 Feb 2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning Ling Guo Hao Wu Wenwen Zhou Yan Wang Tao Zhou UQCV 13 11 0 07 Feb 2023
A neural operator-based surrogate solver for free-form electromagnetic inverse design Yannick Augenstein T. Repän C. Rockstuhl AI4CE 16 28 0 04 Feb 2023
Convolutional Neural Operators for robust and accurate learning of PDEs Bogdan Raonić Roberto Molinaro Tim De Ryck Tobias Rohner Francesca Bartolucci Rima Alaifari Siddhartha Mishra Emmanuel de Bezenac AAML 24 83 0 02 Feb 2023
Learning Functional Transduction Mathieu Chalvidal Thomas Serre Rufin VanRullen AI4CE 30 2 0 01 Feb 2023
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs Nathan Gaby X. Ye Haomin Zhou 11 6 0 31 Jan 2023
Physics-constrained 3D Convolutional Neural Networks for Electrodynamics A. Scheinker R. Pokharel 16 15 0 31 Jan 2023
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning Hrishikesh Viswanath Md Ashiqur Rahman Abhijeet Vyas Andrey Shor Beatriz Medeiros Stephanie Hernandez S. Prameela Aniket Bera PINN AI4CE 42 4 0 30 Jan 2023
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators Christian Moya Guang Lin Tianqiao Zhao Meng Yue 27 8 0 29 Jan 2023
TransNet: Transferable Neural Networks for Partial Differential Equations Zezhong Zhang F. Bao L. Ju Guannan Zhang 11 3 0 27 Jan 2023
Random Grid Neural Processes for Parametric Partial Differential Equations A. Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 20 11 0 26 Jan 2023
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems Z. Y. Wan Leonardo Zepeda-Núnez Anudhyan Boral Fei Sha BDL AI4CE 11 13 0 25 Jan 2023
Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life Kazuma Kobayashi S. B. Alam 19 49 0 17 Jan 2023
L-HYDRA: Multi-Head Physics-Informed Neural Networks Zongren Zou George Karniadakis AI4CE 18 26 0 05 Jan 2023
Metalearning generalizable dynamics from trajectories Qiaofeng Li Tianyi Wang V. Roychowdhury M. Jawed AI4CE 38 10 0 03 Jan 2023
Deep Learning and Computational Physics (Lecture Notes) Deep Ray Orazio Pinti Assad A. Oberai PINN AI4CE 19 7 0 03 Jan 2023
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation Ning Liu Yue Yu Huaiqian You Neeraj Tatikola AI4CE 13 23 0 29 Dec 2022
Guiding continuous operator learning through Physics-based boundary constraints Nadim Saad Gaurav Gupta S. Alizadeh Danielle C. Maddix AI4CE 40 20 0 14 Dec 2022
Reliable extrapolation of deep neural operators informed by physics or sparse observations Min Zhu Handi Zhang Anran Jiao George Karniadakis Lu Lu 42 91 0 13 Dec 2022
Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations Wuzhe Xu Yulong Lu Li Wang 11 33 0 09 Dec 2022
Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations Yemo Li Yiwen Pang Bin Shan AI4CE 24 3 0 08 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 18 34 0 06 Dec 2022
WarpPINN: Cine-MR image registration with physics-informed neural networks Pablo Arratia López Hernán Mella S. Uribe D. Hurtado F. Sahli Costabal 12 15 0 22 Nov 2022
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems Xiongbin Yan Z. Xu Zheng Ma 6 2 0 22 Nov 2022
Physics-Informed Koopman Network Yuying Liu A. Sholokhov Hassan Mansour S. Nabi AI4CE 23 3 0 17 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 23 89 0 15 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 48 0 14 Nov 2022
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows Ivan Zanardi Simone Venturi M. Panesi AI4CE 57 17 0 27 Oct 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 24 17 0 27 Oct 2022
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 12 8 0 26 Oct 2022
Bayesian deep learning framework for uncertainty quantification in high dimensions Jeahan Jung Minseok Choi BDL UQCV 13 1 0 21 Oct 2022
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems Lianghao Cao Thomas O'Leary-Roseberry Prashant K. Jha J. Oden Omar Ghattas 19 26 0 06 Oct 2022
Random Weight Factorization Improves the Training of Continuous Neural Representations Sifan Wang Hanwen Wang Jacob H. Seidman P. Perdikaris 21 9 0 03 Oct 2022
Solving Coupled Differential Equation Groups Using PINO-CDE Wenhao Ding Qing He Hanghang Tong Qingjing Wang Ping Wang OOD AI4CE 27 4 0 01 Oct 2022
Implicit Neural Spatial Representations for Time-dependent PDEs Honglin Chen Rundi Wu E. Grinspun Changxi Zheng Peter Yichen Chen AI4CE 25 33 0 30 Sep 2022
Transformer Meets Boundary Value Inverse Problems Ruchi Guo Shuhao Cao Long Chen MedIm 28 20 0 29 Sep 2022
GeONet: a neural operator for learning the Wasserstein geodesic Andrew Gracyk Xiaohui Chen OT 16 2 0 28 Sep 2022
Variationally Mimetic Operator Networks Dhruv V. Patel Deep Ray M. Abdelmalik T. Hughes Assad A. Oberai 41 23 0 26 Sep 2022
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 80 0 08 Sep 2022
Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems Sebastian Kaltenbach P. Perdikaris P. Koutsourelakis 10 23 0 06 Sep 2022
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning Ben Adcock Juan M. Cardenas N. Dexter 25 8 0 25 Aug 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 25 35 0 25 Aug 2022
G2Φnet: Relating Genotype and Biomechanical Phenotype of Tissues with Deep Learning Enrui Zhang B. Spronck J. Humphrey George Karniadakis AI4CE 28 9 0 21 Aug 2022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs A. Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 23 17 0 09 Aug 2022
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers Namgyu Kang Byeonghyeon Lee Youngjoon Hong S. Yun Eunbyung Park PINN AI4CE 16 13 0 26 Jul 2022
Multiscale Neural Operator: Learning Fast and Grid-independent PDE Solvers Björn Lütjens Catherine H. Crawford C. Watson C. Hill Dava Newman AI4CE 11 9 0 23 Jul 2022