OpenAlex | Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data

Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data

Work

Year: 2021

Type: article

Abstract: Data-driven discovery of partial differential equations (PDEs) has attracted increasing attention in recent years. Although significant progress has been made, certain unresolved issues remain. For ex... more

Source: Journal of Computational Physics

Authors Hao Xu, Dongxiao Zhang, Nanzhe Wang

Institutions Peking University, Southern University of Science and Technology, Peng Cheng Laboratory

Cites: 33

Cited by: 28

Related to: 10

FWCI: 2.706

Citation percentile (by year/subfield): 99.99

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

APC paid (est): $3,750

Funders National Natural Science Foundation of China, National Natural Science Foundation of China, National Natural Science Foundation of China, National Natural Science Foundation of China, National Major Science and Technology Projects of China +3 more

Grant IDS 51520105005, 2017ZX05049-003, 2017ZX05009-005, U1663208, 51520105005 +3 more