10 citations · 13 across the 3 of their papers we have counts for
4 papers
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg +4
This work is the first to employ and adapt the image-to-image translation concept based on conditional generative adversarial networks (cGAN) towards learning a forward and an inve…
Choice of Interior Penalty Coefficient for Interior Penalty Discontinuous Galerkin Method for Biot's System by Employing Machine Learning
Sanghyun Lee, Teeratorn Kadeethum, Hamidreza M. Nick
In this paper, the optimal choice of the interior penalty parameter of the discontinuous Galerkin finite element methods for both the elliptic problems and the Biot's systems are s…
Physics-informed Neural Networks for Solving Inverse Problems of Nonlinear Biot's Equations: Batch Training
Teeratorn Kadeethum, Thomas M Jørgensen, Hamidreza M Nick
In biomedical engineering, earthquake prediction, and underground energy harvesting, it is crucial to indirectly estimate the physical properties of porous media since the direct m…
Physics-informed Neural Networks for Solving Nonlinear Diffusivity and Biot's equations
Teeratorn Kadeethum, Thomas M Jorgensen, Hamidreza M Nick
This paper presents the potential of applying physics-informed neural networks for solving nonlinear multiphysics problems, which are essential to many fields such as biomedical en…