Roger G. Ghanem

Orcid: 0000-0002-1890-920X

Affiliations:
  • University of Southern California, Los Angeles, USA


According to our database1, Roger G. Ghanem authored at least 46 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials.
Reliab. Eng. Syst. Saf., July, 2023

2022
Drivers Learn City-Scale Intra-Daily Dynamic Equilibrium.
IEEE Trans. Intell. Transp. Syst., 2022

Projection pursuit adaptation on polynomial chaos expansions.
CoRR, 2022

2021
Normal-Bundle Bootstrap.
SIAM J. Math. Data Sci., 2021

Data-based Discovery of Governing Equations.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020
Demand, Supply, and Performance of Street-Hail Taxi.
IEEE Trans. Intell. Transp. Syst., 2020

Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset.
Stat. Comput., 2020

Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets.
CoRR, 2020

2019
Compressive sensing adaptation for polynomial chaos expansions.
J. Comput. Phys., 2019

Entropy-based closure for probabilistic learning on manifolds.
J. Comput. Phys., 2019

Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds.
J. Comput. Phys., 2019

Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset.
CoRR, 2019

Data-driven discovery of free-form governing differential equations.
CoRR, 2019

2018
The Stochastic Quasi-chemical Model for Bacterial Growth: Variational Bayesian Parameter Update.
J. Nonlinear Sci., 2018

2017
Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound.
SIAM/ASA J. Uncertain. Quantification, 2017

Reduced Wiener Chaos representation of random fields via basis adaptation and projection.
J. Comput. Phys., 2017

Polynomial chaos representation of databases on manifolds.
J. Comput. Phys., 2017

Homogeneous chaos basis adaptation for design optimization under uncertainty: Application to the oil well placement problem.
Artif. Intell. Eng. Des. Anal. Manuf., 2017

Uncertainty quantification for engineering design.
Artif. Intell. Eng. Des. Anal. Manuf., 2017

2016
Data-driven probability concentration and sampling on manifold.
J. Comput. Phys., 2016

2015
Probabilistic Approach to NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge Problem.
J. Aerosp. Inf. Syst., 2015

2014
Hierarchical Schur complement preconditioner for the stochastic Galerkin finite element methods : Dedicated to Professor Ivo Marek on the occasion of his 80th birthday.
Numer. Linear Algebra Appl., 2014

Basis adaptation in homogeneous chaos spaces.
J. Comput. Phys., 2014

Multiscale Stochastic Representation in High-Dimensional Data Using Gaussian Processes with Implicit Diffusion Metrics.
Proceedings of the Dynamic Data-Driven Environmental Systems Science, 2014

2013
Hybrid Sampling/Spectral Method for Solving Stochastic Coupled Problems.
SIAM/ASA J. Uncertain. Quantification, 2013

Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata.
Entropy, 2013

2012
Accelerating agent-based computation of complex urban systems.
Int. J. Geogr. Inf. Sci., 2012

2010
Identification of Bayesian posteriors for coefficients of chaos expansions.
J. Comput. Phys., 2010

Efficient Monte Carlo computation of Fisher information matrix using prior information.
Comput. Stat. Data Anal., 2010

2009
A Bounded Random Matrix Approach for Stochastic Upscaling.
Multiscale Model. Simul., 2009

Polynomial chaos representation of spatio-temporal random fields from experimental measurements.
J. Comput. Phys., 2009

2008
Asymptotic Sampling Distribution for Polynomial Chaos Representation from Data: A Maximum Entropy and Fisher Information Approach.
SIAM J. Sci. Comput., 2008

2007
Multi-Resolution-Analysis Scheme for Uncertainty Quantification in Chemical Systems.
SIAM J. Sci. Comput., 2007

An efficient calculation of Fisher information matrix: Monte Carlo approach using prior information.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007

2006
On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data.
J. Comput. Phys., 2006

Ultrasound Monitoring of Tissue Ablation Via Deformation Model and Shape Priors.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2006

Domain Decompostion Of Stochastic PDEs and its Parallel.
Proceedings of the 20th Annual International Symposium on High Performance Computing Systems and Applications (HPCS 2006), 2006

Asymptotic Sampling Distribution for Polynomial Chaos Representation of Data: A Maximum Entropy and Fisher information approach.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006

2005
Error Estimation in the Spatial Discretization of Multiscale Bridging Models.
Multiscale Model. Simul., 2005

A Multiscale Data Assimilation with the Ensemble Kalman Filter.
Multiscale Model. Simul., 2005

An equation-free, multiscale approach to uncertainty quantification.
Comput. Sci. Eng., 2005

2004
Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure.
SIAM J. Sci. Comput., 2004

Natural Convection in a Closed Cavity under Stochastic Non-Boussinesq Conditions.
SIAM J. Sci. Comput., 2004

Special Issue on Uncertainty Quantification.
SIAM J. Sci. Comput., 2004

Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes.
SIAM J. Sci. Comput., 2004

Orthogonal representations of stochastic processes and their propagation in mechanics.
Proceedings of the 43rd IEEE Conference on Decision and Control, 2004


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