In this study, we investigate the feasibility of utilizing deep learning technique to construct preconditioners for iterative matrix solvers. A neural network (NN) is proposed to simulate the ...

Time-varying algebraic Riccati equations (TAREs) indeed play a crucial role in science and engineering with widespread applications. This research combines the advantages of zeroing neural network ...

Python module for predicting density, heat capacities and speed of sound of pure fluids using Peng-Robinson, (Soave-)Redlich-Kwong and Lee-Kesler equations of state.

Python Implementation of Ordinary Differential Equations Solvers using Hybrid Physics-informed Neural Networks This repository is provided as a tutorial for the implementation of integration ...