B. Debusschere

发表

Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes

Habib N. Najm, Roger G. Ghanem, Omar M. Knio, 2005, SIAM J. Sci. Comput..

STUDY OF SAMPLE DISPERSION MECHANISMS IN AN ELECTROOSMOTICALLY PUMPED MICROCHANNEL

O. L. Maître, H. Najm, O. Knio, 2003 .

Protein labeling reactions in electrochemical microchannel flow: Numerical simulation and uncertainty propagation

O. L. Maître, H. Najm, O. Knio, 2003 .

DIMENSIONALITY REDUCTION FOR COMPLEX MODELS VIA BAYESIAN COMPRESSIVE SENSING

Peter E. Thornton, Cosmin Safta, Khachik Sargsyan, 2014 .

Spectral methods for parametric sensitivity in stochastic dynamical systems.

H. Najm, B. Debusschere, D. Kim, 2007, Biophysical journal.

Uncertainty quantification in chemical systems

Y. Marzouk, H. Najm, B. Debusschere, 2009 .

Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. II. Uncertain potential parameters.

R. Jones, O. Knio, B. Debusschere, 2013, The Journal of chemical physics.

Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. I. Sensitivity to physical parameters of the pore.

O. Knio, B. Debusschere, R. Jones, 2013, The Journal of chemical physics.

Quadrature Methods for the Calculation of Subgrid Microphysics Moments

V. Larson, B. Debusschere, M. Salloum, 2015 .

Parallel Domain Decomposition Strategies for Stochastic Elliptic Equations Part A: Local KL Representations

O. L. Maître, O. Knio, B. Debusschere, 2017 .

DATA-FREE INFERENCE OF UNCERTAIN PARAMETERS IN CHEMICAL MODELS

R. D. Berry, H. Najm, B. Debusschere, 2014 .

Uncertainty quantification for large-scale ocean circulation predictions.

H. Najm, B. Debusschere, K. Sargsyan, 2010 .

Turbulent scalar transport mechanisms in plane channel and Couette flows

Bert J. Debusschere, Christopher J. Rutland, C. Rutland, 2004 .

Sources of Cell-to-cell Variability in Canonical Nuclear Factor-κB (NF-κB) Signaling Pathway Inferred from Single Cell Dynamic Images*

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2011, The Journal of Biological Chemistry.

Uncertainty Quantification Toolkit (UQTk)

Cosmin Safta, Khachik Sargsyan, Bert J. Debusschere, 2015 .

Spectral Representation and Reduced Order Modeling of Stochastic Reaction Networks

H. Najm, B. Debusschere, K. Sargsyan, 2022 .

Partial Differential Equations Preconditioner Resilient to Soft and Hard Faults

Cosmin Safta, Khachik Sargsyan, Francesco Rizzi, 2016, 2015 IEEE International Conference on Cluster Computing.

Risk assessment of climate systems for national security.

T. Trucano, H. Najm, J. Overfelt, 2012 .

Accuracy of tail regions in uncertain climate model.

H. Najm, B. Debusschere, K. Sargsyan, 2010 .

Uncertainty Quantification given Discontinuous Climate Model Response and a Limited Number of Model Runs

H. Najm, B. Debusschere, K. Sargsyan, 2010 .

Parameter Estimation with Missing Data.

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2013 .

Quantification of Uncertainty in Extreme Scale Computations (QUEST).

Cosmin Safta, Michael S. Eldred, Habib N. Najm, 2012 .

Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

Peter E. Thornton, Cosmin Safta, Khachik Sargsyan, 2014 .

Uncertainty Quantification in a Reacting Electrochemical Microchannel Flow Model

Habib N. Najm, Omar M. Knio, Bert J. Debusschere, 2002 .

A multigrid solver for two-dimensional stochastic diffusion equations

Habib N. Najm, Omar M. Knio, Bert J. Debusschere, 2003 .

Computational study of band-crossing reactions

R. Ghanem, H. Najm, O. Knio, 2004, Journal of Microelectromechanical Systems.

Bayesian neural networks using magnetic tunnel junction-based probabilistic in-memory computing

Christopher H. Bennett, S. Agarwal, B. Debusschere, 2022, Frontiers in Nanotechnology.

Calibration and Comparison of Climate Models: Accounting for Structural and Discretization Error [Poster]

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2016 .

Uncertainty Quantification in Multiscale Atomistic-Continuum Models.

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2011 .

Computational singular perturbation with non-parametric tabulation of slow manifolds for time integration of stiff chemical kinetics

Habib N. Najm, Mauro Valorani, Bert J. Debusschere, 2012 .

Inference of Chemical Model Parameters given Partial Information.

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2013 .

Partial Differential Equations Solver Resilient to Soft and Hard Faults.

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2015 .

Probabilistic Approaches for Communication Avoidance and Resilience in Exascale Simulations.

Habib N. Najm, Bert J. Debusschere, H. Najm, 2013 .

Components for atomistic-to-continuum multiscale modeling of flow in micro- and nanofluidic systems

Habib N. Najm, Bert J. Debusschere, Helgi Adalsteinsson, 2008, Sci. Program..

Bayesian Inference of Spectral Expansions for Predictability Assessment in Stochastic Reaction Networks

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2009 .

Sparse surrogate model construction via compressive sensing.

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2013 .

Computational Frameworks for Advanced Combustion Simulations

Habib N. Najm, Bert J. Debusschere, R. Armstrong, 2011 .

Uncertainty Quantification in Climate Modeling

H. Najm, B. Debusschere, K. Sargsyan, 2010 .

An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty

S. Agarwal, B. Debusschere, T. Xiao, 2022, 2210.10780.

Spectral Representation and Reduced Order Modeling of the Dynamics of Stochastic Reaction Networks via Adaptive Data Partitioning

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2009, SIAM J. Sci. Comput..

Fundamental issues in the representation and propagation of uncertain equation of state information in shock hydrodynamics

William J. Rider, Allen C. Robinson, Robert Dan Berry, 2013 .

Exploring the interplay of resilience and energy consumption for a task-based partial differential equations preconditioner

Cosmin Safta, Khachik Sargsyan, Francesco Rizzi, 2016, Parallel Comput..

Quantitative Uncertainty Assessment and Numerical Simulation of Micro-Fluid Systems

Habib N. Najm, Olivier LeMaitre, Omar M. Knio, 2005 .

How a Quantum Computer Could Quantify Uncertainty in Microkinetic Models.

B. Debusschere, Eric A. Walker, A. Becerra, 2021, The journal of physical chemistry letters.

Parallel Domain Decomposition Strategies for Stochastic Elliptic Equations Part B: Accelerated Monte Carlo Sampling with Local PC Expansions

Francesco Rizzi, Paul Mycek, Omar M. Knio, 2018, SIAM J. Sci. Comput..

Intrusive Polynomial ChaosMethods for Forward Uncertainty Propagation

Bert Debusschere, B. Debusschere, 2016 .

Data-free inference of the joint distribution of uncertain model parameters

Habib N. Najm, Bert J. Debusschere, Helgi Adalsteinsson, 2010, J. Comput. Phys..

Eigenvalues of the Jacobian of a Galerkin-Projected Uncertain ODE System

R. D. Berry, BENJAMIN E. SONDAY, ROBERT D. BERRY, 2011, SIAM J. Sci. Comput..

Fault Resilient Domain Decomposition Preconditioner for PDEs

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2015, SIAM J. Sci. Comput..

Uncertainty Quantification given Discontinuous Model Response and a Limited Number of Model Runs

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2012, SIAM J. Sci. Comput..

Uncertainty Quantification in MD Simulations. Part I: Forward Propagation

F. RIZZI, H. N. NAJM, B. J. DEBUSSCHERE, 2012, Multiscale Model. Simul..

Hybrid discrete/continuum algorithms for stochastic reaction networks

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2015, J. Comput. Phys..

Spectral stochastic uncertainty quantification in chemical systems

O P Le Maître, O M Knio, R. Ghanem, 2004 .

Co-design Center for Exascale Machine Learning Technologies (ExaLearn)

Satoshi Matsuoka, Rajeev Thakur, Shantenu Jha, 2021, Int. J. High Perform. Comput. Appl..

Natural Convection in a Closed Cavity under Stochastic Non-Boussinesq Conditions

Habib N. Najm, Omar M. Knio, Bert J. Debusschere, 2005, SIAM J. Sci. Comput..

A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs

Cosmin Safta, Khachik Sargsyan, Francesco Rizzi, 2017, Comput. Phys. Commun..

Uncertainty Quantification in MD Simulations. Part II: Bayesian Inference of Force-Field Parameters

Khachik Sargsyan, Habib N. Najm, Francesco Rizzi, 2012, Multiscale Model. Simul..

Multiparameter Spectral Representation of Noise-Induced Competence in Bacillus Subtilis

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Machine Learning Surrogates of a Fuel Matrix Degradation Process Model for Performance Assessment of a Nuclear Waste Repository

L. Swiler, Kyung Won Chang, B. Debusschere, 2023, Nuclear Technology.

EXPLORATION OF MULTIFIDELITY APPROACHES FOR UNCERTAINTY QUANTIFICATION IN NETWORK APPLICATIONS

Gianluca Geraci, Laura Painton Swiler, Jonathan Crussell, 2019, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019).

An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty

S. Agarwal, B. Debusschere, T. Xiao, 2022, ArXiv.

Measurements of friction, heat transfer, and mass transfer in a severely outgassing tube bank

K. W. Ragland, B. Debusschere, 1998 .

UQTk Version 3.1.2 User Manual.

Khachik Sargsyan, Mohammad Khalil, Xiaoshu Zeng, 2016 .

Probabilistic Methods for Sensitivity Analysis and Calibration in the NASA Challenge Problem

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2015, J. Aerosp. Inf. Syst..

Uncertainty Quantification in the Presence of Limited Climate Model Data with Discontinuities

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2009, 2009 IEEE International Conference on Data Mining Workshops.

Quantifying Sampling Noise and Parametric Uncertainty in Atomistic-to-Continuum Simulations Using Surrogate Models

Khachik Sargsyan, Habib N. Najm, Bert J. Debusschere, 2015, Multiscale Model. Simul..

Time Integration of Reacting Flows with CSP Tabulation

Y. Marzouk, M. Frenklach, H. Najm, 2009 .

Surrogate Construction and Dimensionality Reduction via Bayesian Compressive Sensing.

Cosmin Safta, Khachik Sargsyan, Habib N. Najm, 2013 .

Sparse Polynomial Chaos Surrogate for ACME Land Model via Iterative Bayesian Compressive Sensing

Khachik Sargsyan, Daniel M. Ricciuto, Cosmin Safta, 2015 .

Automated Generation of Tabular Equations of State with Uncertainty Information.

Bert J. Debusschere, Allen C. Robinson, John H. Carpenter, 2015 .