Akil Narayan

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 111

Top Venues

Publications

Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
Subsampling of Parametric Models with Bifidelity Boosting. SIAM/ASA J. Uncertain. Quantification 12 (2) (2024)
Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe
Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS (2024)
Yanlai Chen, Yajie Ji, Akil Narayan, Zhenli Xu
TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs. CoRR (2024)
Ankur, Ram Jiwari, Akil Narayan
Conformal Finite Element Methods for Nonlinear Rosenau-Burgers-Biharmonic Models. CoRR (2024)
Matthew Lowery, John Turnage, Zachary Morrow, John D. Jakeman, Akil Narayan, Shandian Zhe, Varun Shankar
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning. CoRR (2024)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. 477 (2023)
Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Meta-Learning with Adjoint Methods. AISTATS (2023)
Yiming Xu, Akil Narayan
Budget-limited distribution learning in multifidelity problems. Numerische Mathematik 153 (1) (2023)
Jess D. Tate, Zexin Liu, Jake A. Bergquist, Sumientra Rampersad, Dan White, Chantel Charlebois, Lindsay C. Rupp, Dana H. Brooks, Rob S. MacLeod, Akil Narayan
UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines. J. Open Source Softw. 8 (90) (2023)
Jake A. Bergquist, Matthias Lange, Brian Zenger, Benjamin A. Orkild, Eric Paccione, Eugene Kwan, Bram Hunt, Jiawei Dong, Rob S. MacLeod, Akil Narayan, Ravi Ranjan
Uncertainty Quantification of the Effect of Variable Conductivity in Ventricular Fibrotic Regions on Ventricular Tachycardia. CinC (2023)
Shibo Li, Xin Yu, Wei W. Xing, Mike Kirby, Akil Narayan, Shandian Zhe
Multi-Resolution Active Learning of Fourier Neural Operators. CoRR (2023)
Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML (2023)
Akil Narayan, Zexin Liu, Jake A. Bergquist, Chantel Charlebois, Sumientra Rampersad, Lindsay C. Rupp, Dana H. Brooks, Dan White, Jess D. Tate, Rob S. MacLeod
UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering. Comput. Biol. Medicine 152 (2023)
Justin Baker, Elena Cherkaev, Akil Narayan, Bao Wang
Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs. J. Sci. Comput. 95 (2) (2023)
Zexin Liu, Akil Narayan
A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials. SIAM J. Sci. Comput. 45 (3) (2023)
Vidhi Zala, Akil Narayan, Robert M. Kirby
Convex optimization-based structure-preserving filter for multidimensional finite element simulations. J. Comput. Phys. 492 (2023)
Benjamin A. Orkild, Jake A. Bergquist, Eric Paccione, Matthias Lange, Eugene Kwan, Bram Hunt, Rob S. MacLeod, Akil Narayan, Ravi Ranjan
A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations. CinC (2023)
Lindsay C. Rupp, Anna Busatto, Jake A. Bergquist, Karli Gillette, Akil Narayan, Gernot Plank, Rob S. MacLeod
Uncertainty Quantification of Fiber Orientation and Epicardial Activation. CinC (2023)
Ruijian Han, Akil Narayan, Yiming Xu
An approximate control variates approach to multifidelity distribution estimation. CoRR (2023)
Yiming Xu, Akil Narayan
Randomized weakly admissible meshes. J. Approx. Theory 285 (2023)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Energy Stable and Structure-Preserving Schemes for the Stochastic Galerkin Shallow Water Equations. CoRR (2023)
Anna Busatto, Lindsay C. Rupp, Karli Gillette, Akil Narayan, Gernot Plank, Rob S. MacLeod
Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification. CinC (2023)
Vidhi Zala, Akil Narayan, Robert M. Kirby
Convex Optimization-Based Structure-Preserving Filter For Multidimensional Finite Element Simulations. CoRR (2022)
Jake A. Bergquist, Lindsay C. Rupp, Anna Busatto, Ben Orkild, Brian Zenger, Wilson Good, Jaume Coll-Font, Akil Narayan, Jess D. Tate, Dana H. Brooks, Rob S. MacLeod
Heart Position Uncertainty Quantification in the Inverse Problem of ECGI. CinC (2022)
Narimane Gassa, Machteld J. Boonstra, Beata Ondrusova, Jana Svehlíková, Dana H. Brooks, Akil Narayan, Ali S. Rababah, Peter M. van Dam, Rob S. MacLeod, Jess D. Tate, Nejib Zemzemi
Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization. CinC (2022)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. 451 (2022)
Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. J. Sci. Comput. 90 (2) (2022)
Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. CoRR (2022)
Beata Ondrusova, Machteld J. Boonstra, Jana Svehlíková, Dana H. Brooks, Peter M. van Dam, Ali S. Rababah, Akil Narayan, Rob S. MacLeod, Nejib Zemzemi, Jess D. Tate
The Effect of Segmentation Variability in Forward ECG Simulation. CinC (2022)
Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
A Bandit-Learning Approach to Multifidelity Approximation. SIAM J. Sci. Comput. 44 (1) (2022)
Jarom D. Hogue, Robert M. Kirby, Akil Narayan
Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures. CoRR (2022)
Ryleigh A. Moore, Akil Narayan
Adaptive density tracking by quadrature for stochastic differential equations. Appl. Math. Comput. 431 (2022)
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
Nonparametric Embeddings of Sparse High-Order Interaction Events. CoRR (2022)
Jess D. Tate, Nejib Zemzemi, Shireen Y. Elhabian, Beáta Ondrusová, Machteld J. Boonstra, Peter M. van Dam, Akil Narayan, Dana H. Brooks, Rob S. MacLeod
Segmentation Uncertainty Quantification in Cardiac Propagation Models. CinC (2022)
Xiajun Jiang, Jess Tate, Jake Bergquist, Akil Narayan, Rob S. MacLeod, Linwei Wang
Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI. CinC (2022)
Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer, Akil Narayan
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference. J. Sci. Comput. 91 (1) (2022)
Zexin Liu, Akil Narayan
A Stieltjes algorithm for generating multivariate orthogonal polynomials. CoRR (2022)
Justin Baker, Hedi Xia, Yiwei Wang, Elena Cherkaev, Akil Narayan, Long Chen, Jack Xin, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs. CoRR (2022)
Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Bayesian Continuous-Time Tucker Decomposition. ICML (2022)
Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby, Akil Narayan
GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices. CoRR (2022)
Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR (2022)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Hyperbolicity-preserving and well-balanced stochastic Galerkin method for two-dimensional shallow water equations. J. Comput. Phys. 452 (2022)
Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
Nonparametric Embeddings of Sparse High-Order Interaction Events. ICML (2022)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs. SIAM J. Sci. Comput. 43 (2) (2021)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. CoRR (2021)
Akil Narayan, Liang Yan, Tao Zhou
Optimal design for kernel interpolation: Applications to uncertainty quantification. J. Comput. Phys. 430 (2021)
Yanlai Chen, Lijie Ji, Akil Narayan, Zhenli Xu
L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations. J. Sci. Comput. 87 (1) (2021)
Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
A bandit-learning approach to multifidelity approximation. CoRR (2021)
Zexin Liu, Akil Narayan
On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials. J. Sci. Comput. 88 (3) (2021)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. SIAM J. Sci. Comput. 43 (6) (2021)
Jake A. Bergquist, Brian Zenger, Lindsay C. Rupp, Akil Narayan, Jess D. Tate, Rob S. MacLeod
Uncertainty Quantification in Simulations of Myocardial Ischemia. CinC (2021)
Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer, Akil Narayan
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference. CoRR (2021)
Lindsay C. Rupp, Jake A. Bergquist, Brian Zenger, Karli Gillette, Akil Narayan, Jess D. Tate, Gernot Plank, Rob S. MacLeod
The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification. CinC (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR (2021)
Zexin Liu, Akil Narayan
On the computation of recurrence coefficients for univariate orthogonal polynomials. CoRR (2021)
Yiming Xu, Akil Narayan
Budget-limited distribution learning in multifidelity problems. CoRR (2021)
Mani Razi, Robert M. Kirby, Akil Narayan
Kernel optimization for Low-Rank Multi-Fidelity Algorithms. CoRR (2021)
Shibo Li, Zheng Wang, Akil Narayan, Robert Michael Kirby, Shandian Zhe
Meta-Learning with Adjoint Methods. CoRR (2021)
Roland Pulch, Akil Narayan
Sensitivity analysis of random linear dynamical systems using quadratic outputs. J. Comput. Appl. Math. 387 (2021)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Non-Dissipative and Structure-Preserving Emulators via Spherical Optimization. CoRR (2021)
Akil Narayan, Liang Yan, Tao Zhou
Optimal design for kernel interpolation: applications to uncertainty quantification. CoRR (2021)
Yiming Xu, Akil Narayan
Randomized weakly admissible meshes. CoRR (2021)
Ryleigh A. Moore, Akil Narayan
Adaptive Density Tracking by Quadrature for Stochastic Differential Equations. CoRR (2021)
Jess D. Tate, Wilson W. Good, Nejib Zemzemi, Machteld J. Boonstra, Peter M. van Dam, Dana H. Brooks, Akil Narayan, Rob S. MacLeod
Uncertainty Quantification of the Effects of Segmentation Variability in ECGI. FIMH (2021)
Roland Pulch, Akil Narayan, Tatjana Stykel
Sensitivity analysis of random linear differential-algebraic equations using system norms. J. Comput. Appl. Math. 397 (2021)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Two-Dimensional Shallow Water Equations. CoRR (2021)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations. SIAM J. Sci. Comput. 43 (2) (2021)
Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. CoRR (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR (2021)
Yiming Xu, Akil Narayan, Hoang Tran, Clayton G. Webster
Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing. CoRR (2020)
Roohallah Khatami, Masood Parvania, Akil Narayan
Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization. IEEE Trans. Smart Grid 11 (1) (2020)
Yanlai Chen, Lijie Ji, Akil Narayan, Zhenli Xu
L1-based reduced over collocation and hyper reduction for steady state and time-dependent nonlinear equations. CoRR (2020)
Kyle M. Burk, Akil Narayan, Joseph A. Orr
Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points. CoRR (2020)
Dihan Dai, Yekaterina Epshteyn, Akil Narayan
Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations. CoRR (2020)
Vidhi Zala, Mike Kirby, Akil Narayan
Structure-Preserving Function Approximation via Convex Optimization. SIAM J. Sci. Comput. 42 (5) (2020)
Varun Shankar, Grady B. Wright, Akil Narayan
A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds. SIAM J. Sci. Comput. 42 (4) (2020)
Ling Guo, Akil Narayan, Yongle Liu, Tao Zhou
Sparse approximation of data-driven Polynomial Chaos expansions: an induced sampling approach. CoRR (2020)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Generation of nested quadrature rules for generic weight functions via numerical optimization: Application to sparse grids. J. Comput. Phys. 400 (2020)
Ling Guo, Akil Narayan, Tao Zhou
Constructing Least-Squares Polynomial Approximations. SIAM Rev. 62 (2) (2020)
Lindsay C. Rupp, Zexin Liu, Jake A. Bergquist, Sumientra Rampersad, Dan White, Jess D. Tate, Dana H. Brooks, Akil Narayan, Rob S. MacLeod
Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations. CinC (2020)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-preserving function approximation via convex optimization. CoRR (2020)
Roland Pulch, Akil Narayan
Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs. SIAM J. Sci. Comput. 41 (4) (2019)
Varun Shankar, Grady B. Wright, Akil Narayan
A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds. CoRR (2019)
Mani Razi, Robert M. Kirby, Akil Narayan
Fast predictive multi-fidelity prediction with models of quantized fidelity levels. J. Comput. Phys. 376 (2019)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Convergence Acceleration for Time-Dependent Parametric Multifidelity Models. SIAM J. Numer. Anal. 57 (3) (2019)
Barbara M. Johnston, Akil Narayan, Peter R. Johnston
A Comparison of Methods for Examining the Effect of Uncertainty in the Conductivities in a Model of Partial Thickness Ischaemia. CinC (2019)
Daniel J. Perry, Robert M. Kirby, Akil Narayan, Ross T. Whitaker
Allocation Strategies for High Fidelity Models in the Multifidelity Regime. SIAM/ASA J. Uncertain. Quantification 7 (1) (2019)
Lun Yang, Yi Qin, Akil Narayan, Peng Wang
Data assimilation for models with parametric uncertainty. J. Comput. Phys. 396 (2019)
Harbir Antil, Yanlai Chen, Akil Narayan
Reduced Basis Methods for Fractional Laplace Equations via Extension. SIAM J. Sci. Comput. 41 (6) (2019)
Yanlai Chen, Jiahua Jiang, Akil Narayan
A robust error estimator and a residual-free error indicator for reduced basis methods. Comput. Math. Appl. 77 (7) (2019)
Ming Cheng, Akil Narayan, Yi Qin, Peng Wang, Xinghui Zhong, Xueyu Zhu
An efficient solver for cumulative density function-based solutions of uncertain kinematic wave models. J. Comput. Phys. 382 (2019)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Numerical Integration in Multiple Dimensions with Designed Quadrature. SIAM J. Sci. Comput. 40 (4) (2018)
Ling Guo, Akil Narayan, Tao Zhou
-minimization for sparse approximation of polynomial chaos expansions. J. Comput. Phys. 367 (2018)
Roohallah Khatami, Masood Parvania, Pramod P. Khargonekar, Akil Narayan
Continuous-Time Stochastic Modeling and Estimation of Electricity Load. CDC (2018)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Numerical Integration in Multiple Dimensions with Designed Quadrature. CoRR (2018)
Varun Shankar, Akil Narayan, Robert M. Kirby
RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces. J. Comput. Phys. 373 (2018)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Parametric Topology Optimization with Multi-Resolution Finite Element Models. CoRR (2018)
Ling Guo, Akil Narayan, Liang Yan, Tao Zhou
Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation. SIAM J. Sci. Comput. 40 (1) (2018)
Jerrad Hampton, Hillary R. Fairbanks, Akil Narayan, Alireza Doostan
Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction. J. Comput. Phys. 368 (2018)
Ben Adcock, Anyi Bao, John D. Jakeman, Akil Narayan
Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations. SIAM/ASA J. Uncertain. Quantification 6 (4) (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Akil Narayan