Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Marzouk, Youssef M"'
Autor:
Menhorn, Friedrich, Geraci, Gianluca, Seidl, D. Thomas, Marzouk, Youssef M., Eldred, Michael S., Bungartz, Hans-Joachim
Optimization is a key tool for scientific and engineering applications, however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization und
Externí odkaz:
http://arxiv.org/abs/2305.03103
This article presents a general approximation-theoretic framework to analyze measure transport algorithms for probabilistic modeling. A primary motivating application for such algorithms is sampling -- a central task in statistical inference and gene
Externí odkaz:
http://arxiv.org/abs/2302.13965
Langevin dynamics are widely used in sampling high-dimensional, non-Gaussian distributions whose densities are known up to a normalizing constant. In particular, there is strong interest in unadjusted Langevin algorithms (ULA), which directly discret
Externí odkaz:
http://arxiv.org/abs/2302.07227
Autor:
Baptista, Ricardo, Cao, Lianghao, Chen, Joshua, Ghattas, Omar, Li, Fengyi, Marzouk, Youssef M., Oden, J. Tinsley
We consider the Bayesian calibration of models describing the phenomenon of block copolymer (BCP) self-assembly using image data produced by microscopy or X-ray scattering techniques. To account for the random long-range disorder in BCP equilibrium s
Externí odkaz:
http://arxiv.org/abs/2206.11343
We discuss approaches to computing eigenfunctions of the Ornstein--Uhlenbeck (OU) operator in more than two dimensions. While the spectrum of the OU operator and theoretical properties of its eigenfunctions have been well characterized in previous re
Externí odkaz:
http://arxiv.org/abs/2110.09229
We introduce a novel geometry-informed irreversible perturbation that accelerates convergence of the Langevin algorithm for Bayesian computation. It is well documented that there exist perturbations to the Langevin dynamics that preserve its invarian
Externí odkaz:
http://arxiv.org/abs/2108.08247
Autor:
Baptista, Ricardo, Cao, Lianghao, Chen, Joshua, Ghattas, Omar, Li, Fengyi, Marzouk, Youssef M., Oden, J. Tinsley
Publikováno v:
In Journal of Computational Physics 15 April 2024 503
The estimation of rare event or failure probabilities in high dimensions is of interest in many areas of science and technology. We consider problems where the rare event is expressed in terms of a computationally costly numerical model. Importance s
Externí odkaz:
http://arxiv.org/abs/2006.05496
Autor:
Gu, Chen, Mok, Ulrich, Marzouk, Youssef M., Gomez, Germán A Prieto, Sheibani, Farrokh, Evans, J. Brian, Hager, Bradford H.
Publikováno v:
Geophysical Journal International, 2019, ggz568
Acoustic emission (AE) is a widely used technology to study source mechanisms and material properties during high-pressure rock failure experiments. It is important to understand the physical quantities that acoustic emission sensors measure, as well
Externí odkaz:
http://arxiv.org/abs/1906.10098
Autor:
Feng, Chi, Marzouk, Youssef M.
We develop a new computational approach for "focused" optimal Bayesian experimental design with nonlinear models, with the goal of maximizing expected information gain in targeted subsets of model parameters. Our approach considers uncertainty in the
Externí odkaz:
http://arxiv.org/abs/1903.11187