DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

8 October 2019

Papers citing "DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators"

50 / 207 papers shown

Title
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Exciton-Polariton Condensates: A Fourier Neural Operator Approach S. T. Sathujoda Yuan Wang Kanishk Gandhi 11 0 0 27 Sep 2023
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points Gianluca Fabiani N. Evangelou Tianqi Cui J. M. Bello-Rivas Cristina P. Martin-Linares Constantinos Siettos Ioannis G. Kevrekidis 30 2 0 25 Sep 2023
$A numerical approach for the fractional Laplacian via deep neural networks$ A numerical approach for the fractional Laplacian via deep neural networks Nicolás Valenzuela 19 3 0 30 Aug 2023
GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks Xinquan Huang T. Alkhalifah 23 12 0 10 Aug 2023
Branched Latent Neural Maps M. Salvador Alison Lesley Marsden 30 4 0 04 Aug 2023
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks N. R. Franco S. Fresca Filippo Tombari Andrea Manzoni AI4CE 19 16 0 03 Aug 2023
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators Xiang Huang Zhuoyuan Li Hongsheng Liu Zidong Wang Hongye Zhou Bin Dong Bei Hua AI4TS AI4CE 16 1 0 26 Jul 2023
Capturing Local Temperature Evolution during Additive Manufacturing through Fourier Neural Operators Jiangce Chen Wenzhuo Xu Martha Baldwin Björn Nijhuis T. Boogaard Noelia Grande Gutiérrez S. Narra Christopher McComb AI4CE 8 2 0 04 Jul 2023
Accelerated primal-dual methods with enlarged step sizes and operator learning for nonsmooth optimal control problems Yongcun Song Xiaoming Yuan Hangrui Yue AI4CE 8 2 0 01 Jul 2023
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning Pu Ren N. Benjamin Erichson Shashank Subramanian Omer San Z. Lukić Michael W. Mahoney Michael W. Mahoney 34 13 0 24 Jun 2023
Neural Astrophysical Wind Models Dustin D. Nguyen 11 2 0 20 Jun 2023
Embedding stochastic differential equations into neural networks via dual processes Naoki Sughishita Jun Ohkubo 7 1 0 08 Jun 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 30 27 0 29 May 2023
Generative Adversarial Reduced Order Modelling Dario Coscia N. Demo G. Rozza GAN AI4CE 34 5 0 25 May 2023
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction Hao Wu Wei Xion Fan Xu Xian-Sheng Hua C. L. Philip Chen Xiansheng Hua AI4TS 14 27 0 19 May 2023
PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems S. Mao R. Dong Lu Lu K. M. Yi Sifan Wang P. Perdikaris 6 16 0 18 May 2023
Physics Informed Token Transformer for Solving Partial Differential Equations Cooper Lorsung Zijie Li Amir Barati Farimani AI4CE 24 15 0 15 May 2023
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs F. Pichi B. Moya J. Hesthaven AI4CE 28 51 0 15 May 2023
Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs Pau Batlle Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 13 17 0 08 May 2023
A Direct Sampling-Based Deep Learning Approach for Inverse Medium Scattering Problems Jianfeng Ning Fuqun Han Jun Zou 26 11 0 29 Apr 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 16 10 0 27 Apr 2023
Nonlocality and Nonlinearity Implies Universality in Operator Learning S. Lanthaler Zong-Yi Li Andrew M. Stuart 16 16 0 26 Apr 2023
In-Context Operator Learning with Data Prompts for Differential Equation Problems Liu Yang Siting Liu Tingwei Meng Stanley J. Osher 27 54 0 17 Apr 2023
A Framework for Combustion Chemistry Acceleration with DeepONets Anuj Kumar T. Echekki 14 1 0 06 Apr 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 24 20 0 30 Mar 2023
Learning Flow Functions from Data with Applications to Nonlinear Oscillators Miguel Aguiar Amritam Das Karl H. Johansson 8 2 0 29 Mar 2023
The transformative potential of machine learning for experiments in fluid mechanics Ricardo Vinuesa Steven L. Brunton B. McKeon AI4CE 13 68 0 28 Mar 2023
GNN-based physics solver for time-independent PDEs R. J. Gladstone H. Rahmani V. Suryakumar Hadi Meidani M. DÉlia A. Zareei AI4CE 20 15 0 28 Mar 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 18 24 0 27 Mar 2023
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs Miroslav Krstic Luke Bhan Yuanyuan Shi 33 28 0 18 Mar 2023
On the effectiveness of neural priors in modeling dynamical systems Sameera Ramasinghe Hemanth Saratchandran Violetta Shevchenko Simon Lucey 24 2 0 10 Mar 2023
Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations Xiongye Xiao De-An Cao Ruochen Yang Gaurav Gupta Gengshuo Liu Chenzhong Yin R. Balan P. Bogdan 58 9 0 04 Mar 2023
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks K. Michałowska S. Goswami George Karniadakis S. Riemer-Sørensen AI4CE 15 15 0 03 Mar 2023
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance Panos Pantidis Habiba Eldababy Christopher Miguel Tagle M. Mobasher 16 20 0 03 Mar 2023
DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design Z. Liu Yixing Li Jing Hu Xinling Yu Shi-En Shiau Xin Ai Zhiyu Zeng Zheng-Wei Zhang AI4CE 25 16 0 25 Feb 2023
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems Yingzhi Xia Qifeng Liao Jinglai Li 11 2 0 22 Feb 2023
Variational Autoencoding Neural Operators Jacob H. Seidman Georgios Kissas George J. Pappas P. Perdikaris DRL AI4CE 22 7 0 20 Feb 2023
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 12 8 0 20 Feb 2023
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks Mohamed Aziz Bhouri M. Joly Robert Yu S. Sarkar P. Perdikaris BDL UQCV AI4CE 11 1 0 14 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
Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations Arnulf Jentzen Adrian Riekert Philippe von Wurstemberger 11 1 0 07 Feb 2023
Randomized prior wavelet neural operator for uncertainty quantification Shailesh Garg S. Chakraborty UQCV BDL 8 1 0 02 Feb 2023
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils K. Shukla Vivek Oommen Ahmad Peyvan Michael Penwarden L. Bravo A. Ghoshal Robert M. Kirby George Karniadakis 27 19 0 02 Feb 2023
Continuous Spatiotemporal Transformers Antonio H. O. Fonseca E. Zappala J. O. Caro David van Dijk 8 7 0 31 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
Neural Inverse Operators for Solving PDE Inverse Problems Roberto Molinaro Yunan Yang Bjorn Engquist Siddhartha Mishra AI4CE 19 35 0 26 Jan 2023
Solving Inverse Physics Problems with Score Matching Benjamin Holzschuh S. Vegetti Nils Thuerey DiffM 11 8 0 24 Jan 2023
Deep Learning and Computational Physics (Lecture Notes) Deep Ray Orazio Pinti Assad A. Oberai PINN AI4CE 17 7 0 03 Jan 2023
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions F. Bonnet Jocelyn Ahmed Mazari Paola Cinnella Patrick Gallinari AI4CE 25 54 0 15 Dec 2022