OpenAlex | Approximation rates of DeepONets for learning operators arising from advection–diffusion equations

Approximation rates of DeepONets for learning operators arising from advection–diffusion equations

Work

Year: 2022

Type: article

Source: Neural Networks

Authors Beichuan Deng, Yeonjong Shin, Lu Lu, Zhongqiang Zhang, George Em Karniadakis

Institutions Worcester Polytechnic Institute, Brown University, University of Pennsylvania

Cites: 37

Cited by: 50

Related to: 10

FWCI: 6.546

Citation percentile (by year/subfield): 99.98

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders U.S. Department of Energy, U.S. Department of Energy, Brown University, Worcester Polytechnic Institute, Air Force Office of Scientific Research

Grant IDS HR00112090062, DE-SC0019453, , , FA9550-20-1-0056