Akil Narayan

CoRR, 2024

2023

Convex optimization-based structure-preserving filter for multidimensional finite element simulations.

[BibT_eX]

[DOI]

Vidhi Zala

J. Comput. Phys., November, 2023

UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines.

[BibT_eX]

[DOI]

J. Open Source Softw., October, 2023

A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials.

[BibT_eX]

[DOI]

Zexin Liu

SIAM J. Sci. Comput., June, 2023

Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs.

[BibT_eX]

[DOI]

J. Sci. Comput., May, 2023

A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs.

[BibT_eX]

[DOI]

J. Comput. Phys., March, 2023

Randomized weakly admissible meshes.

[BibT_eX]

[DOI]

Yiming Xu

J. Approx. Theory, January, 2023

Budget-limited distribution learning in multifidelity problems.

[BibT_eX]

[DOI]

Yiming Xu

Numerische Mathematik, 2023

Energy Stable and Structure-Preserving Schemes for the Stochastic Galerkin Shallow Water Equations.

[BibT_eX]

[DOI]

CoRR, 2023

Multi-Resolution Active Learning of Fourier Neural Operators.

[BibT_eX]

[DOI]

CoRR, 2023

An approximate control variates approach to multifidelity distribution estimation.

[BibT_eX]

[DOI]

Ruijian Han

Yiming Xu

CoRR, 2023

UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2023

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Uncertainty Quantification of Fiber Orientation and Epicardial Activation.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2023

A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2023

Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2023

Uncertainty Quantification of the Effect of Variable Conductivity in Ventricular Fibrotic Regions on Ventricular Tachycardia.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2023

Meta-Learning with Adjoint Methods.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Bandit-Learning Approach to Multifidelity Approximation.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2022

Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference.

[BibT_eX]

[DOI]

J. Sci. Comput., 2022

Fast Barycentric-Based Evaluation Over Spectral/hp Elements.

[BibT_eX]

[DOI]

J. Sci. Comput., 2022

Multifidelity modeling for Physics-Informed Neural Networks (PINNs).

[BibT_eX]

[DOI]

J. Comput. Phys., 2022

Hyperbolicity-preserving and well-balanced stochastic Galerkin method for two-dimensional shallow water equations.

[BibT_eX]

[DOI]

J. Comput. Phys., 2022

Quadrature Sampling of Parametric Models with Bi-fidelity Boosting.

[BibT_eX]

[DOI]

CoRR, 2022

Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems.

[BibT_eX]

[DOI]

CoRR, 2022

Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs.

[BibT_eX]

[DOI]

CoRR, 2022

Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures.

[BibT_eX]

[DOI]

Jarom D. Hogue

CoRR, 2022

Learning POD of Complex Dynamics Using Heavy-ball Neural ODEs.

[BibT_eX]

[DOI]

CoRR, 2022

GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices.

[BibT_eX]

[DOI]

CoRR, 2022

Adaptive density tracking by quadrature for stochastic differential equations.

[BibT_eX]

[DOI]

Ryleigh A. Moore

Appl. Math. Comput., 2022

Nonparametric Embeddings of Sparse High-Order Interaction Events.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Bayesian Continuous-Time Tucker Decomposition.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Segmentation Uncertainty Quantification in Cardiac Propagation Models.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2022

The Effect of Segmentation Variability in Forward ECG Simulation.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2022

Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2022

Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2022

Heart Position Uncertainty Quantification in the Inverse Problem of ECGI.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2022

2021

Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods.

[BibT_eX]

[DOI]

Vidhi Zala

SIAM J. Sci. Comput., 2021

Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2021

Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2021

On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials.

[BibT_eX]

[DOI]

Zexin Liu

J. Sci. Comput., 2021

L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations.

[BibT_eX]

[DOI]

J. Sci. Comput., 2021

Optimal design for kernel interpolation: Applications to uncertainty quantification.

[BibT_eX]

[DOI]

Liang Yan

J. Comput. Phys., 2021

Sensitivity analysis of random linear differential-algebraic equations using system norms.

[BibT_eX]

[DOI]

Roland Pulch

Tatjana Stykel

J. Comput. Appl. Math., 2021

Sensitivity analysis of random linear dynamical systems using quadratic outputs.

[BibT_eX]

[DOI]

Roland Pulch

J. Comput. Appl. Math., 2021

Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach.

[BibT_eX]

[DOI]

CoRR, 2021

Meta-Learning with Adjoint Methods.

[BibT_eX]

[DOI]

CoRR, 2021

Non-Dissipative and Structure-Preserving Emulators via Spherical Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Optimal design for kernel interpolation: applications to uncertainty quantification.

[BibT_eX]

[DOI]

Liang Yan

CoRR, 2021

Kernel optimization for Low-Rank Multi-Fidelity Algorithms.

[BibT_eX]

[DOI]

Mani Razi

CoRR, 2021

Uncertainty Quantification of the Effects of Segmentation Variability in ECGI.

[BibT_eX]

[DOI]

Proceedings of the Functional Imaging and Modeling of the Heart, 2021

The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

Uncertainty Quantification in Simulations of Myocardial Ischemia.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

2020

Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization.

[BibT_eX]

[DOI]

Roohallah Khatami

Masood Parvania

IEEE Trans. Smart Grid, 2020

Structure-Preserving Function Approximation via Convex Optimization.

[BibT_eX]

[DOI]

Vidhi Zala

Mike Kirby

SIAM J. Sci. Comput., 2020

A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds.

[BibT_eX]

[DOI]

Varun Shankar

Grady B. Wright

SIAM J. Sci. Comput., 2020

Constructing Least-Squares Polynomial Approximations.

[BibT_eX]

[DOI]

Ling Guo

SIAM Rev., 2020

Generation of nested quadrature rules for generic weight functions via numerical optimization: Application to sparse grids.

[BibT_eX]

[DOI]

J. Comput. Phys., 2020

Sparse approximation of data-driven Polynomial Chaos expansions: an induced sampling approach.

[BibT_eX]

[DOI]

CoRR, 2020

Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points.

[BibT_eX]

[DOI]

Kyle M. Burk

Joseph A. Orr

CoRR, 2020

Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing.

[BibT_eX]

[DOI]

CoRR, 2020

Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations.

[BibT_eX]

[DOI]

Proceedings of the Computing in Cardiology, 2020

2019

Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs.

[BibT_eX]

[DOI]

Roland Pulch

SIAM J. Sci. Comput., 2019

Reduced Basis Methods for Fractional Laplace Equations via Extension.

[BibT_eX]

[DOI]

Harbir Antil

SIAM J. Sci. Comput., 2019

Convergence Acceleration for Time-Dependent Parametric Multifidelity Models.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., 2019

Allocation Strategies for High Fidelity Models in the Multifidelity Regime.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, 2019

Data assimilation for models with parametric uncertainty.

[BibT_eX]

[DOI]

J. Comput. Phys., 2019

Fast predictive multi-fidelity prediction with models of quantized fidelity levels.

[BibT_eX]

[DOI]

Mani Razi

J. Comput. Phys., 2019

An efficient solver for cumulative density function-based solutions of uncertain kinematic wave models.

[BibT_eX]

[DOI]

J. Comput. Phys., 2019

A robust error estimator and a residual-free error indicator for reduced basis methods.

[BibT_eX]

[DOI]

Jiahua Jiang

Comput. Math. Appl., 2019

A Comparison of Methods for Examining the Effect of Uncertainty in the Conductivities in a Model of Partial Thickness Ischaemia.

[BibT_eX]

[DOI]

Barbara M. Johnston

Peter R. Johnston

Proceedings of the 46th Computing in Cardiology, 2019

2018

Numerical Integration in Multiple Dimensions with Designed Quadrature.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2018

Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2018

Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations.

[BibT_eX]

[DOI]

SIAM/ASA J. Uncertain. Quantification, 2018

RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces.

[BibT_eX]

[DOI]

Varun Shankar

J. Comput. Phys., 2018

Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction.

[BibT_eX]

[DOI]

J. Comput. Phys., 2018

A gradient enhanced ℓ1-minimization for sparse approximation of polynomial chaos expansions.

[BibT_eX]

[DOI]

Ling Guo

J. Comput. Phys., 2018

Parametric Topology Optimization with Multi-Resolution Finite Element Models.

[BibT_eX]

[DOI]

CoRR, 2018

Continuous-Time Stochastic Modeling and Estimation of Electricity Load.

[BibT_eX]

[DOI]

Roohallah Khatami

Masood Parvania

Pramod P. Khargonekar

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2017

Stochastic Collocation Methods via ℓ1 Minimization Using Randomized Quadratures.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2017

Numerical Computation of Weil-Peterson Geodesics in the Universal Teichmüller Space.

[BibT_eX]

[DOI]

Matt Feiszli

SIAM J. Imaging Sci., 2017

A Christoffel function weighted least squares algorithm for collocation approximations.

[BibT_eX]

[DOI]

Math. Comput., 2017

Effectively Subsampled Quadratures for Least Squares Polynomial Approximations.

[BibT_eX]

[DOI]

Pranay Seshadri

Sankaran Mahadevan

SIAM/ASA J. Uncertain. Quantification, 2017

Offline-Enhanced Reduced Basis Method Through Adaptive Construction of the Surrogate Training Set.

[BibT_eX]

[DOI]

Jiahua Jiang

J. Sci. Comput., 2017

Sequential data assimilation with multiple nonlinear models and applications to subsurface flow.

[BibT_eX]

[DOI]

Lun Yang

Peng Wang

J. Comput. Phys., 2017

2016

A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm.

[BibT_eX]

[DOI]

Jiahua Jiang

SIAM/ASA J. Uncertain. Quantification, 2016

A Reduced Radial Basis Function Method for Partial Differential Equations on Irregular Domains.

[BibT_eX]

[DOI]

J. Sci. Comput., 2016

2015

Weighted discrete least-squares polynomial approximation using randomized quadratures.

[BibT_eX]

[DOI]

J. Comput. Phys., 2015

2014

Multivariate Discrete Least-Squares Approximations with a New Type of Collocation Grid.

[BibT_eX]

[DOI]

Zhiqiang Xu

SIAM J. Sci. Comput., 2014

Adaptive Leja Sparse Grid Constructions for Stochastic Collocation and High-Dimensional Approximation.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2014

A Stochastic Collocation Algorithm with Multifidelity Models.

[BibT_eX]

[DOI]

Claude Jeffrey Gittelson

SIAM J. Sci. Comput., 2014

Approximating the Weil-Petersson Metric Geodesics on the Universal Teichmüller Space by Singular Solutions.

[BibT_eX]

[DOI]

Sergey Kushnarev

SIAM J. Imaging Sci., 2014

Computational Aspects of Stochastic Collocation with Multifidelity Models.

[BibT_eX]

[DOI]

Xueyu Zhu

SIAM/ASA J. Uncertain. Quantification, 2014

2013

Constructing Nested Nodal Sets for Multivariate Polynomial Interpolation.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2013

Minimal multi-element stochastic collocation for uncertainty quantification of discontinuous functions.

[BibT_eX]

[DOI]

J. Comput. Phys., 2013

A generalization of the Wiener rational basis functions on infinite intervals, Part II - Numerical investigation.

[BibT_eX]

[DOI]

Akil C. Narayan

Jan S. Hesthaven

J. Comput. Appl. Math., 2013

2012

Stochastic Collocation Methods on Unstructured Grids in High Dimensions via Interpolation.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2012

Sequential data assimilation with multiple models.

[BibT_eX]

[DOI]

Youssef M. Marzouk

J. Comput. Phys., 2012

2011

A generalization of the Wiener rational basis functions on infinite intervals: Part I-derivation and properties.

[BibT_eX]

[DOI]