1 citations · 1 across the 1 of their papers we have counts for
3 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…
Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks
Jan Niklas Fuhg, Michele Marino, Nikolaos Bouklas
Hierarchical computational methods for multiscale mechanics such as the FE and FE-FFT methods are generally accompanied by high computational costs. Data-driven approaches are…
Model-data-driven constitutive responses: application to a multiscale computational framework
Jan Niklas Fuhg, Christoph Boehm, Nikolaos Bouklas +3
Computational multiscale methods for analyzing and deriving constitutive responses have been used as a tool in engineering problems because of their ability to combine information…