no code implementations • 5 Aug 2020 • Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh, Valeria Andreoli, Thomas Vandeputte, Liping Wang
We present a Bayesian approach to identify optimal transformations that map model input points to low dimensional latent variables.
no code implementations • 23 Dec 2019 • Panagiotis Tsilifis, Iason Papaioannou, Daniel Straub, Fabio Nobile
The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations.
no code implementations • 6 Jan 2018 • Panagiotis Tsilifis, Xun Huan, Cosmin Safta, Khachik Sargsyan, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm, Roger G. Ghanem
Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ.
no code implementations • 30 May 2015 • Panagiotis Tsilifis, Roger G. Ghanem, Paris Hajali
We propose a framework where a lower bound of the expected information gain is used as an alternative design criterion.
2 code implementations • 21 Oct 2014 • Panagiotis Tsilifis, Ilias Bilionis, Ioannis Katsounaros, Nicholas Zabaras
The classical approach to inverse problems is based on the optimization of a misfit function.