1 citations · 1 across the 1 of their papers we have counts for
2 papers
math.NA2024★ 1 cited
Separable Physics-Informed Neural Networks for the solution of elasticity problems
Vasiliy A. Es'kin, Danil V. Davydov, Julia V. Gur'eva +2
A method for solving elasticity problems based on separable physics-informed neural networks (SPINN) in conjunction with the deep energy method (DEM) is presented. Numerical experi…
math.NA2023
About optimal loss function for training physics-informed neural networks under respecting causality
Vasiliy A. Es'kin, Danil V. Davydov, Ekaterina D. Egorova +3
A method is presented that allows to reduce a problem described by differential equations with initial and boundary conditions to the problem described only by differential equatio…