67 citations · 170 across the 7 of their papers we have counts for
5 papers · 1 filter
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes
Panagiotis Tsilifis, Piyush Pandita, Sayan Ghosh +3
We present a Bayesian approach to identify optimal transformations that map model input points to low dimensional latent variables. The "projection" mapping consists of an orthonor…
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines
Panagiotis Tsilifis, Iason Papaioannou, Daniel Straub +1
The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations. These challenge…
Compressive sensing adaptation for polynomial chaos expansions
Panagiotis Tsilifis, Xun Huan, Cosmin Safta +5
Basis adaptation in Homogeneous Chaos spaces rely on a suitable rotation of the underlying Gaussian germ. Several rotations have been proposed in the literature resulting in adapta…
Efficient Bayesian experimentation using an expected information gain lower bound
Panagiotis Tsilifis, Roger G. Ghanem, Paris Hajali
Experimental design is crucial for inference where limitations in the data collection procedure are present due to cost or other restrictions. Optimal experimental designs determin…
Variational Reformulation of Bayesian Inverse Problems
Panagiotis Tsilifis, Ilias Bilionis, Ioannis Katsounaros +1
The classical approach to inverse problems is based on the optimization of a misfit function. Despite its computational appeal, such an approach suffers from many shortcomings, e.g…