1 citations · 1 across the 3 of their papers we have counts for
3 papers
About rectified sigmoid function for enhancing the accuracy of Physics-Informed Neural Networks
Vasiliy A. Es'kin, Alexey O. Malkhanov, Mikhail E. Smorkalov
The article is devoted to the study of neural networks with one hidden layer and a modified activation function for solving physical problems. A rectified sigmoid activation functi…
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…
Catenary and Mercator projection
Mikhail A. Akhukov, Vasiliy A. Es'kin, Mikhail E. Smorkalov
The Mercator projection is sometimes confused with another mapping technique, specifically the central cylindrical projection, which projects the Earth's surface onto a cylinder ta…