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

Science Advances (Sci Adv), 2021

19 March 2021

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

29 / 379 papers shown

Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery

137

07 Feb 2022

Spectrally Adapted Physics-Informed Neural Networks for Solving Unbounded Domain Problems

Mingtao Xia

Lucas Böttcher

T. Chou

197

06 Feb 2022

Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEsJournal of Scientific Computing (J. Sci. Comput.), 2022

175

05 Feb 2022

Constructing coarse-scale bifurcation diagrams from spatio-temporal observations of microscopic simulations: A parsimonious machine learning approachJournal of Scientific Computing (J. Sci. Comput.), 2022

Evangelos Galaris

Gianluca Fabiani

I. Gallos

Ioannis G. Kevrekidis

Constantinos Siettos

AI4CE

263

31 Jan 2022

Pseudo-Differential Neural Operator: Generalized Fourier Neural Operator for Learning Solution Operators of Partial Differential Equations

J. Shin

Jae Yong Lee

H. Hwang

312

28 Jan 2022

Learning Operators with Coupled AttentionJournal of machine learning research (JMLR), 2022

Georgios Kissas

Jacob H. Seidman

Leonardo Ferreira Guilhoto

V. Preciado

George J. Pappas

P. Perdikaris

255

135

04 Jan 2022

Frame invariance and scalability of neural operators for partial differential equationsCommunications in Computational Physics (Commun. Comput. Phys.), 2021

100

28 Dec 2021

Physics-Informed Neural Operator for Learning Partial Differential Equations

Kamyar Azizzadenesheli

Anima Anandkumar

AI4CE

604

605

06 Nov 2021

An extended physics informed neural network for preliminary analysis of parametric optimal control problems

209

26 Oct 2021

A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs

260

26 Oct 2021

Fast PDE-constrained optimization via self-supervised operator learning

Sizhuang He

Mohamed Aziz Bhouri

P. Perdikaris

211

25 Oct 2021

Improved architectures and training algorithms for deep operator networks

321

135

04 Oct 2021

Multiwavelet-based Operator Learning for Differential Equations

Gaurav Gupta

Xiongye Xiao

P. Bogdan

384

271

28 Sep 2021

Learning in Sinusoidal Spaces with Physics-Informed Neural Networks

Abhishek Gupta

164

108

20 Sep 2021

Discretization-independent surrogate modeling over complex geometries using hypernetworks and implicit representations

298

14 Sep 2021

Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural networkJournal of the Royal Society Interface (J. R. Soc. Interface), 2021

222

25 Aug 2021

Neural Operator: Learning Maps Between Function Spaces

Nikola B. Kovachki

Zong-Yi Li

Burigede Liu

Kamyar Azizzadenesheli

786

558

19 Aug 2021

A physics-informed variational DeepONet for predicting the crack path in brittle materials

164

261

16 Aug 2021

Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equationsAdvances in Computational Mathematics (Adv. Comput. Math.), 2021

205

328

16 Jul 2021

MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEsCommunications in Computational Physics (Commun. Comput. Phys.), 2021

284

08 Jul 2021

Physics-Guided Deep Learning for Dynamical Systems: A Survey

Rui Wang

Rose Yu

AI4CE PINN

490

02 Jul 2021

Closed-form Continuous-time Neural ModelsNature Machine Intelligence (Nat. Mach. Intell.), 2021

Ramin Hasani

Daniela Rus

271

142

25 Jun 2021

Long-time integration of parametric evolution equations with physics-informed DeepONetsJournal of Computational Physics (JCP), 2021

Sizhuang He

P. Perdikaris

AI4CE

217

144

09 Jun 2021

Encoding physics to learn reaction-diffusion processesNature Machine Intelligence (Nat. Mach. Intell.), 2021

Yang Liu

270

143

09 Jun 2021

Learning particle swarming models from data with Gaussian processesMathematics of Computation (Math. Comp.), 2021

383

04 Jun 2021

Choose a Transformer: Fourier or GalerkinNeural Information Processing Systems (NeurIPS), 2021

Shuhao Cao

437

344

31 May 2021

Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical SolverMathematical and Scientific Machine Learning (MSML), 2021

263

23 May 2021

One-shot learning for solution operators of partial differential equationsNature Communications (Nat Commun), 2021

381

06 Apr 2021

Deep neural network for solving differential equations motivated by Legendre-Galerkin approximationInternational Journal of Numerical Analysis and Modeling (IJNAM), 2020

183

24 Oct 2020