Panagiotis (Panos) Tsilifis
Panagiotis (Panos) Tsilifis
General Electric Vernova Advanced Research
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Compressive sensing adaptation for polynomial chaos expansions
P Tsilifis, X Huan, C Safta, K Sargsyan, G Lacaze, JC Oefelein, HN Najm, ...
Journal of Computational Physics 380, 29-47, 2019
Reduced Wiener Chaos representation of random fields via basis adaptation and projection
P Tsilifis, RG Ghanem
Journal of Computational Physics 341, 102-120, 2017
Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound
P Tsilifis, RG Ghanem, P Hajali
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 30-62, 2017
Bayesian adaptation of chaos representations using variational inference and sampling on geodesics
P Tsilifis, RG Ghanem
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018
Homogeneous chaos basis adaptation for design optimization under uncertainty: Application to the oil well placement problem
C Thimmisetty, P Tsilifis, R Ghanem
Ai Edam 31 (3), 265-276, 2017
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes
P Tsilifis, P Pandita, S Ghosh, V Andreoli, T Vandeputte, L Wang
Computer Methods in Applied Mechanics and Engineering 386, 114147, 2021
Computationally efficient variational approximations for Bayesian inverse problems
P Tsilifis, I Bilionis, I Katsounaros, N Zabaras
Journal of Verification, Validation and Uncertainty Quantification 1 (3), 031004, 2016
Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes
P Pandita, P Tsilifis, NM Awalgaonkar, I Bilionis, J Panchal
Computer Methods in Applied Mechanics and Engineering 385, 114007, 2021
Sparse Polynomial Chaos expansions using variational relevance vector machines
P Tsilifis, I Papaioannou, D Straub, F Nobile
Journal of Computational Physics 416, 109498, 2020
A Multilevel Stochastic Gradient method for PDE-constrained Optimal Control Problems with uncertain parameters
M Martin, F Nobile, P Tsilifis
arXiv preprint arXiv:1912.11900, 2019
Gradient-Informed Basis Adaptation for Legendre Chaos Expansions
PA Tsilifis
Journal of Verification, Validation and Uncertainty Quantification 3 (1), 011005, 2018
Markov Chain Monte Carlo Inference of Parametric Dictionaries for Sparse Bayesian Approximations
T Chaspari, A Tsiartas, P Tsilifis, SS Narayanan
IEEE Transactions on Signal Processing 64 (12), 3077-3092, 2016
Scalable fully bayesian gaussian process modeling and calibration with adaptive sequential monte carlo for industrial applications
P Pandita, P Tsilifis, S Ghosh, L Wang
Journal of Mechanical Design 143 (7), 074502, 2021
Cubic-Quintic Long-Range Interactions With Double Well Potentials
PA Tsilifis, PG Kevrekidis, VM Rothos
Journal of Physics A: Mathematical and Theoretical 47 (3), 035201, 2014
Inverse Design under Uncertainty using Conditional Normalizing Flows
P Tsilifis, S Ghosh, V Andreoli
AIAA SCITECH 2022 Forum, 0631, 2022
Dimensionality Reduction for Multi-Fidelity Gaussian Processes using Bayesian Adaptation
P Tsilifis, P Pandita, S Ghosh, L Wang
AIAA Scitech 2021 Forum, 1588, 2021
The stochastic quasi-chemical model for bacterial growth: Variational bayesian parameter update
P Tsilifis, WJ Browning, TE Wood, PK Newton, RG Ghanem
Journal of Nonlinear Science 28, 371-393, 2018
Multi-fidelity metamodeling in turbine blade airfoils via transfer learning on manifolds
K Kontolati, P Tsilifis, S Ghosh, V Andreoli, M Shields, L Wang
AIAA SCITECH 2023 Forum, 0918, 2023
Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds
P Tsilifis, P Pandita, S Ghosh, L Wang
Entropy 24 (9), 1291, 2022
Variational Reformulation of Bayesian Inverse Problems
P Tsilifis, I Bilionis, I Katsounaros, N Zabaras
UNCECOMP 2015, 1st ECCOMAS Thematic Conference on Uncertainty Quantification …, 2015
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