Results 331 to 340 of about 217,226 (371)

A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs

Journal of Computational Physics, 2023
Shandian Zhe, Akil C Narayan
exaly  

Cobordism of PDE's

1991
The main purpose of this interesting paper is to generalize to higher order PDE's some previous results of \textit{J. Eliashberg} [Semin. sud- rhodanien géom. I, 17-31 (1984; Zbl 0542.57024)] concerning the cobordism of the first order PDE's. The paper contains two sections (1. Cobordism and spectral sequences; 2.
openaire   +2 more sources

Deep least-squares methods: An unsupervised learning-based numerical method for solving elliptic PDEs

Journal of Computational Physics, 2020
Zhiqiang Cai, Min Liu
exaly  

The immunomodulatory role of PDEs inhibitors in immune cells: therapeutic implication in rheumatoid arthritis

Pharmacological Research, 2020
Hai-Bin Luo, Ying Xie
exaly  

PDE

2021
openaire   +1 more source

Analysis and Approximation of Mixed-Dimensional PDEs on 3D-1D Domains Coupled with Lagrange Multipliers

SIAM Journal on Numerical Analysis, 2021
Miroslav Kuchta, Federica Laurino, Kent André Mardal   +2 more
exaly  

PDE

2006
openaire   +2 more sources

Clinical and Molecular Genetics of the Phosphodiesterases (PDEs)

Endocrine Reviews, 2014
Anelia Horvath, Faiyaz Ahmad, Constantine A Stratakis   +2 more
exaly  

Learning PDEs

PDEs are considered to be language of physics as they provide mathematical descriptions of a whole range of physical phenomena. The complexity and prohibitive computational cost of traditional physics-based numerical schemes necessitates the search for fast and efficient surrogates, based on machine learning.
openaire   +1 more source

Preserving energy resp. dissipation in numerical PDEs using the “Average Vector Field” method

Journal of Computational Physics, 2012
Robert I Mclachlan
exaly