Akil Narayan

Orcid: 0000-0002-5914-4207

Affiliations:
  • University of Utah, Salt Lake City, UT, USA


According to our database1, Akil Narayan authored at least 103 papers between 2011 and 2024.

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

Timeline

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Bibliography

2024
An Approximate Control Variates Approach to Multifidelity Distribution Estimation.
SIAM/ASA J. Uncertain. Quantification, 2024

Subsampling of Parametric Models with Bifidelity Boosting.
SIAM/ASA J. Uncertain. Quantification, 2024

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation.
CoRR, 2024

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning.
CoRR, 2024

TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs.
CoRR, 2024

Conformal Finite Element Methods for Nonlinear Rosenau-Burgers-Biharmonic Models.
CoRR, 2024

Multi-Resolution Active Learning of Fourier Neural Operators.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Convex optimization-based structure-preserving filter for multidimensional finite element simulations.
J. Comput. Phys., November, 2023

UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines.
J. Open Source Softw., October, 2023

A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials.
SIAM J. Sci. Comput., June, 2023

Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs.
J. Sci. Comput., May, 2023

A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs.
J. Comput. Phys., March, 2023

Randomized weakly admissible meshes.
J. Approx. Theory, January, 2023

Budget-limited distribution learning in multifidelity problems.
Numerische Mathematik, 2023

Energy Stable and Structure-Preserving Schemes for the Stochastic Galerkin Shallow Water Equations.
CoRR, 2023

An approximate control variates approach to multifidelity distribution estimation.
CoRR, 2023

UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering.
Comput. Biol. Medicine, 2023

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Uncertainty Quantification of Fiber Orientation and Epicardial Activation.
Proceedings of the Computing in Cardiology, 2023

A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations.
Proceedings of the Computing in Cardiology, 2023

Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification.
Proceedings of the Computing in Cardiology, 2023

Uncertainty Quantification of the Effect of Variable Conductivity in Ventricular Fibrotic Regions on Ventricular Tachycardia.
Proceedings of the Computing in Cardiology, 2023

Meta-Learning with Adjoint Methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A Bandit-Learning Approach to Multifidelity Approximation.
SIAM J. Sci. Comput., 2022

Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference.
J. Sci. Comput., 2022

Fast Barycentric-Based Evaluation Over Spectral/hp Elements.
J. Sci. Comput., 2022

Multifidelity modeling for Physics-Informed Neural Networks (PINNs).
J. Comput. Phys., 2022

Hyperbolicity-preserving and well-balanced stochastic Galerkin method for two-dimensional shallow water equations.
J. Comput. Phys., 2022

Quadrature Sampling of Parametric Models with Bi-fidelity Boosting.
CoRR, 2022

Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems.
CoRR, 2022

Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs.
CoRR, 2022

Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures.
CoRR, 2022

Learning POD of Complex Dynamics Using Heavy-ball Neural ODEs.
CoRR, 2022

GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices.
CoRR, 2022

Adaptive density tracking by quadrature for stochastic differential equations.
Appl. Math. Comput., 2022

Nonparametric Embeddings of Sparse High-Order Interaction Events.
Proceedings of the International Conference on Machine Learning, 2022

Bayesian Continuous-Time Tucker Decomposition.
Proceedings of the International Conference on Machine Learning, 2022

Segmentation Uncertainty Quantification in Cardiac Propagation Models.
Proceedings of the Computing in Cardiology, 2022

The Effect of Segmentation Variability in Forward ECG Simulation.
Proceedings of the Computing in Cardiology, 2022

Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI.
Proceedings of the Computing in Cardiology, 2022

Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization.
Proceedings of the Computing in Cardiology, 2022

Heart Position Uncertainty Quantification in the Inverse Problem of ECGI.
Proceedings of the Computing in Cardiology, 2022

2021
Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods.
SIAM J. Sci. Comput., 2021

Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs.
SIAM J. Sci. Comput., 2021

Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations.
SIAM J. Sci. Comput., 2021

On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials.
J. Sci. Comput., 2021

L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations.
J. Sci. Comput., 2021

Optimal design for kernel interpolation: Applications to uncertainty quantification.
J. Comput. Phys., 2021

Sensitivity analysis of random linear differential-algebraic equations using system norms.
J. Comput. Appl. Math., 2021

Sensitivity analysis of random linear dynamical systems using quadratic outputs.
J. Comput. Appl. Math., 2021

Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach.
CoRR, 2021

Non-Dissipative and Structure-Preserving Emulators via Spherical Optimization.
CoRR, 2021

Kernel optimization for Low-Rank Multi-Fidelity Algorithms.
CoRR, 2021

Uncertainty Quantification of the Effects of Segmentation Variability in ECGI.
Proceedings of the Functional Imaging and Modeling of the Heart, 2021

The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

Uncertainty Quantification in Simulations of Myocardial Ischemia.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

2020
Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization.
IEEE Trans. Smart Grid, 2020

Structure-Preserving Function Approximation via Convex Optimization.
SIAM J. Sci. Comput., 2020

A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds.
SIAM J. Sci. Comput., 2020

Constructing Least-Squares Polynomial Approximations.
SIAM Rev., 2020

Generation of nested quadrature rules for generic weight functions via numerical optimization: Application to sparse grids.
J. Comput. Phys., 2020

Sparse approximation of data-driven Polynomial Chaos expansions: an induced sampling approach.
CoRR, 2020

Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points.
CoRR, 2020

Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing.
CoRR, 2020

Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations.
Proceedings of the Computing in Cardiology, 2020

2019
Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs.
SIAM J. Sci. Comput., 2019

Reduced Basis Methods for Fractional Laplace Equations via Extension.
SIAM J. Sci. Comput., 2019

Convergence Acceleration for Time-Dependent Parametric Multifidelity Models.
SIAM J. Numer. Anal., 2019

Allocation Strategies for High Fidelity Models in the Multifidelity Regime.
SIAM/ASA J. Uncertain. Quantification, 2019

Data assimilation for models with parametric uncertainty.
J. Comput. Phys., 2019

Fast predictive multi-fidelity prediction with models of quantized fidelity levels.
J. Comput. Phys., 2019

An efficient solver for cumulative density function-based solutions of uncertain kinematic wave models.
J. Comput. Phys., 2019

A robust error estimator and a residual-free error indicator for reduced basis methods.
Comput. Math. Appl., 2019

A Comparison of Methods for Examining the Effect of Uncertainty in the Conductivities in a Model of Partial Thickness Ischaemia.
Proceedings of the 46th Computing in Cardiology, 2019

2018
Numerical Integration in Multiple Dimensions with Designed Quadrature.
SIAM J. Sci. Comput., 2018

Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation.
SIAM J. Sci. Comput., 2018

Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations.
SIAM/ASA J. Uncertain. Quantification, 2018

RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces.
J. Comput. Phys., 2018

Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction.
J. Comput. Phys., 2018

A gradient enhanced <i>ℓ</i><sub>1</sub>-minimization for sparse approximation of polynomial chaos expansions.
J. Comput. Phys., 2018

Parametric Topology Optimization with Multi-Resolution Finite Element Models.
CoRR, 2018

Continuous-Time Stochastic Modeling and Estimation of Electricity Load.
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.
SIAM J. Sci. Comput., 2017

Stochastic Collocation Methods via ℓ<sub>1</sub> Minimization Using Randomized Quadratures.
SIAM J. Sci. Comput., 2017

Numerical Computation of Weil-Peterson Geodesics in the Universal Teichmüller Space.
SIAM J. Imaging Sci., 2017

A Christoffel function weighted least squares algorithm for collocation approximations.
Math. Comput., 2017

Effectively Subsampled Quadratures for Least Squares Polynomial Approximations.
SIAM/ASA J. Uncertain. Quantification, 2017

Offline-Enhanced Reduced Basis Method Through Adaptive Construction of the Surrogate Training Set.
J. Sci. Comput., 2017

Sequential data assimilation with multiple nonlinear models and applications to subsurface flow.
J. Comput. Phys., 2017

2016
A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm.
SIAM/ASA J. Uncertain. Quantification, 2016

A Reduced Radial Basis Function Method for Partial Differential Equations on Irregular Domains.
J. Sci. Comput., 2016

2015
Weighted discrete least-squares polynomial approximation using randomized quadratures.
J. Comput. Phys., 2015

2014
Multivariate Discrete Least-Squares Approximations with a New Type of Collocation Grid.
SIAM J. Sci. Comput., 2014

Adaptive Leja Sparse Grid Constructions for Stochastic Collocation and High-Dimensional Approximation.
SIAM J. Sci. Comput., 2014

A Stochastic Collocation Algorithm with Multifidelity Models.
SIAM J. Sci. Comput., 2014

Approximating the Weil-Petersson Metric Geodesics on the Universal Teichmüller Space by Singular Solutions.
SIAM J. Imaging Sci., 2014

Computational Aspects of Stochastic Collocation with Multifidelity Models.
SIAM/ASA J. Uncertain. Quantification, 2014

2013
Constructing Nested Nodal Sets for Multivariate Polynomial Interpolation.
SIAM J. Sci. Comput., 2013

Minimal multi-element stochastic collocation for uncertainty quantification of discontinuous functions.
J. Comput. Phys., 2013

A generalization of the Wiener rational basis functions on infinite intervals, Part II - Numerical investigation.
J. Comput. Appl. Math., 2013

2012
Stochastic Collocation Methods on Unstructured Grids in High Dimensions via Interpolation.
SIAM J. Sci. Comput., 2012

Sequential data assimilation with multiple models.
J. Comput. Phys., 2012

2011
A generalization of the Wiener rational basis functions on infinite intervals: Part I-derivation and properties.
Math. Comput., 2011


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