Deep learning methods for partial differential equations and related parameter identification problems
Work
Year: 2023
Type: article
Abstract: Recent years have witnessed a growth in mathematics for deep learning—which seeks a deeper understanding of the concepts of deep learning with mathematics and explores how to make it more robust—and ... more
Source: Inverse Problems
Authors Derick Nganyu Tanyu, Jianfeng Ning, Tom Freudenberg, Nick Heilenkötter, Andreas Rademacher +2 more
Institutions Staats- und Universitätsbibliothek Bremen, University of Bremen, Wuhan University, Robert Bosch (Germany)
Cites: 160
Cited by: 23
Related to: 10
FWCI: 5.169
Citation percentile (by year/subfield): 99.98
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Sustainable Development Goal Industry, innovation and infrastructure
Open Access status: hybrid