Akil Narayan - RankMe

136 papers A* 4A 2Journal 115Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Entropy stable reduced order modeling of nonlinear conservation laws using discontinuous Galerkin methods. J. Comput. Phys. Ray Qu, Akil Narayan, Jesse Chan
2026	J	`jnl`	Fast algorithms for least squares problems with Kronecker lower subsets. J. Sci. Comput. Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
2025	J	`jnl`	An Optimal Weighted Least-Squares Method for Operator Learning. CoRR John Turnage, Matthew Lowery, John D. Jakeman, Zachary Morrow, Akil Narayan, Varun Shankar
2025	A*	`conf`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. ICML Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2025	J	`jnl`	Conformal Finite Element Methods for Nonlinear Rosenau-Burgers-Biharmonic Models. J. Sci. Comput. Ankur Ankur, Ram Jiwari, Akil Narayan
2025	J	`jnl`	Efficient and Robust Carathéodory-Steinitz Pruning of Positive Discrete Measures. CoRR Filip Belík, Jesse Chan, Akil Narayan
2025	J	`jnl`	Entropy stable reduced order modeling of nonlinear conservation laws using discontinuous Galerkin methods. CoRR Ray Qu, Akil Narayan, Jesse Chan
2025	J	`jnl`	Greedy Rational Approximation for Frequency-Domain Model Reduction of Parametric LTI Systems. CoRR Filip Belík, Yanlai Chen, Akil Narayan
2025	J	`jnl`	Hybrid least squares for learning functions from highly noisy data. CoRR Ben Adcock, Bernhard Hientzsch, Akil Narayan, Yiming Xu
2025	J	`jnl`	SUPN: Shallow Universal Polynomial Networks. CoRR Zachary Morrow, Michael Penwarden, Brian Chen, Aurya Javeed, Akil Narayan, John D. Jakeman
2024	J	`jnl`	An Approximate Control Variates Approach to Multifidelity Distribution Estimation. SIAM/ASA J. Uncertain. Quantification Ruijian Han, Boris Kramer, Dongjin Lee, Akil Narayan, Yiming Xu
2024	J	`jnl`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. CoRR Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2024	J	`jnl`	Conformal Finite Element Methods for Nonlinear Rosenau-Burgers-Biharmonic Models. CoRR Ankur Ankur, Ram Jiwari, Akil Narayan
2024	J	`jnl`	Energy Stable and Structure-Preserving Algorithms for the Stochastic Galerkin System of 2D Shallow Water Equations. CoRR Yekaterina Epshteyn, Akil Narayan, Yinqian Yu
2024	J	`jnl`	Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning. CoRR Matthew Lowery, John Turnage, Zachary Morrow, John D. Jakeman, Akil Narayan, Shandian Zhe, Varun Shankar
2024	A	`conf`	Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe
2024	J	`jnl`	Subsampling of Parametric Models with Bifidelity Boosting. SIAM/ASA J. Uncertain. Quantification Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
2024	J	`jnl`	TGPT-PINN: Nonlinear model reduction with transformed GPT-PINNs. CoRR Yanlai Chen, Yajie Ji, Akil Narayan, Zhenli Xu
2023	—	`conf`	A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations. CinC Benjamin A. Orkild, Jake A. Bergquist, Eric Paccione, Matthias Lange, Eugene Kwan, Bram Hunt, Rob S. MacLeod, Akil Narayan, Ravi Ranjan
2023	J	`jnl`	A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials. SIAM J. Sci. Comput. Zexin Liu, Akil Narayan
2023	J	`jnl`	A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2023	J	`jnl`	An approximate control variates approach to multifidelity distribution estimation. CoRR Ruijian Han, Akil Narayan, Yiming Xu
2023	J	`jnl`	Budget-limited distribution learning in multifidelity problems. Numerische Mathematik Yiming Xu, Akil Narayan
2023	—	`conf`	Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification. CinC Anna Busatto, Lindsay C. Rupp, Karli Gillette, Akil Narayan, Gernot Plank, Rob S. MacLeod
2023	J	`jnl`	Convex optimization-based structure-preserving filter for multidimensional finite element simulations. J. Comput. Phys. Vidhi Zala, Akil Narayan, Robert M. Kirby
2023	J	`jnl`	Energy Stable and Structure-Preserving Schemes for the Stochastic Galerkin Shallow Water Equations. CoRR Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2023	J	`jnl`	Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs. J. Sci. Comput. Justin M. Baker, Elena Cherkaev, Akil Narayan, Bao Wang
2023	A*	`conf`	Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe
2023	A	`conf`	Meta-Learning with Adjoint Methods. AISTATS Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe
2023	J	`jnl`	Multi-Resolution Active Learning of Fourier Neural Operators. CoRR Shibo Li, Xin Yu, Wei W. Xing, Mike Kirby, Akil Narayan, Shandian Zhe
2023	J	`jnl`	Randomized weakly admissible meshes. J. Approx. Theory Yiming Xu, Akil Narayan
2023	J	`jnl`	UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines. J. Open Source Softw. 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
2023	J	`jnl`	UncertainSCI: Uncertainty quantification for computational models in biomedicine and bioengineering. Comput. Biol. Medicine 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
2023	—	`conf`	Uncertainty Quantification of Fiber Orientation and Epicardial Activation. CinC Lindsay C. Rupp, Anna Busatto, Jake A. Bergquist, Karli Gillette, Akil Narayan, Gernot Plank, Rob S. MacLeod
2023	—	`conf`	Uncertainty Quantification of the Effect of Variable Conductivity in Ventricular Fibrotic Regions on Ventricular Tachycardia. CinC 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
2022	J	`jnl`	A Bandit-Learning Approach to Multifidelity Approximation. SIAM J. Sci. Comput. Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2022	J	`jnl`	A Stieltjes algorithm for generating multivariate orthogonal polynomials. CoRR Zexin Liu, Akil Narayan
2022	J	`jnl`	Adaptive density tracking by quadrature for stochastic differential equations. Appl. Math. Comput. Ryleigh A. Moore, Akil Narayan
2022	A*	`conf`	Bayesian Continuous-Time Tucker Decomposition. ICML Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Convex Optimization-Based Structure-Preserving Filter For Multidimensional Finite Element Simulations. CoRR Vidhi Zala, Akil Narayan, Robert M. Kirby
2022	J	`jnl`	Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures. CoRR Jarom D. Hogue, Robert M. Kirby, Akil Narayan
2022	—	`conf`	Effect of Segmentation Uncertainty on the ECGI Inverse Problem Solution and Source Localization. CinC 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
2022	J	`jnl`	Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. CoRR Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
2022	J	`jnl`	Fast Barycentric-Based Evaluation Over Spectral/hp Elements. J. Sci. Comput. Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
2022	J	`jnl`	GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices. CoRR Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby, Akil Narayan
2022	—	`conf`	Heart Position Uncertainty Quantification in the Inverse Problem of ECGI. CinC 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
2022	J	`jnl`	Hyperbolicity-preserving and well-balanced stochastic Galerkin method for two-dimensional shallow water equations. J. Comput. Phys. Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2022	J	`jnl`	Learning POD of Complex Dynamics Using Heavy-ball Neural ODEs. CoRR Justin M. Baker, Elena Cherkaev, Akil Narayan, Bao Wang
2022	J	`jnl`	Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference. J. Sci. Comput. Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer, Akil Narayan
2022	J	`jnl`	Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2022	A*	`conf`	Nonparametric Embeddings of Sparse High-Order Interaction Events. ICML Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
2022	J	`jnl`	Nonparametric Embeddings of Sparse High-Order Interaction Events. CoRR Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe
2022	J	`jnl`	Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs. CoRR Justin M. Baker, Hedi Xia, Yiwei Wang, Elena Cherkaev, Akil Narayan, Long Chen, Jack Xin, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
2022	—	`conf`	Segmentation Uncertainty Quantification in Cardiac Propagation Models. CinC 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
2022	—	`conf`	The Effect of Segmentation Variability in Forward ECG Simulation. CinC 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
2022	—	`conf`	Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI. CinC Xiajun Jiang, Jess D. Tate, Jake Bergquist, Akil Narayan, Rob S. MacLeod, Linwei Wang
2021	J	`jnl`	A bandit-learning approach to multifidelity approximation. CoRR Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2021	J	`jnl`	Adaptive Density Tracking by Quadrature for Stochastic Differential Equations. CoRR Ryleigh A. Moore, Akil Narayan
2021	J	`jnl`	Budget-limited distribution learning in multifidelity problems. CoRR Yiming Xu, Akil Narayan
2021	J	`jnl`	Fast Barycentric-Based Evaluation Over Spectral/hp Elements. CoRR Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
2021	J	`jnl`	Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations. SIAM J. Sci. Comput. Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2021	J	`jnl`	Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Two-Dimensional Shallow Water Equations. CoRR Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2021	J	`jnl`	Kernel optimization for Low-Rank Multi-Fidelity Algorithms. CoRR Mani Razi, Robert M. Kirby, Akil Narayan
2021	J	`jnl`	L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations. J. Sci. Comput. Yanlai Chen, Lijie Ji, Akil Narayan, Zhenli Xu
2021	J	`jnl`	Meta-Learning with Adjoint Methods. CoRR Shibo Li, Zheng Wang, Akil Narayan, Robert Michael Kirby, Shandian Zhe
2021	J	`jnl`	Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference. CoRR Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer, Akil Narayan
2021	J	`jnl`	Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	J	`jnl`	Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs. SIAM J. Sci. Comput. Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2021	J	`jnl`	Non-Dissipative and Structure-Preserving Emulators via Spherical Optimization. CoRR Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2021	J	`jnl`	On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials. J. Sci. Comput. Zexin Liu, Akil Narayan
2021	J	`jnl`	On the computation of recurrence coefficients for univariate orthogonal polynomials. CoRR Zexin Liu, Akil Narayan
2021	J	`jnl`	Optimal design for kernel interpolation: Applications to uncertainty quantification. J. Comput. Phys. Akil Narayan, Liang Yan, Tao Zhou
2021	J	`jnl`	Optimal design for kernel interpolation: applications to uncertainty quantification. CoRR Akil Narayan, Liang Yan, Tao Zhou
2021	J	`jnl`	Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	J	`jnl`	Randomized weakly admissible meshes. CoRR Yiming Xu, Akil Narayan
2021	J	`jnl`	Sensitivity analysis of random linear differential-algebraic equations using system norms. J. Comput. Appl. Math. Roland Pulch, Akil Narayan, Tatjana Stykel
2021	J	`jnl`	Sensitivity analysis of random linear dynamical systems using quadratic outputs. J. Comput. Appl. Math. Roland Pulch, Akil Narayan
2021	J	`jnl`	Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. SIAM J. Sci. Comput. Vidhi Zala, Robert M. Kirby, Akil Narayan
2021	J	`jnl`	Structure-preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. CoRR Vidhi Zala, Robert M. Kirby, Akil Narayan
2021	—	`conf`	The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification. CinC Lindsay C. Rupp, Jake A. Bergquist, Brian Zenger, Karli Gillette, Akil Narayan, Jess D. Tate, Gernot Plank, Rob S. MacLeod
2021	—	`conf`	Uncertainty Quantification in Simulations of Myocardial Ischemia. CinC Jake A. Bergquist, Brian Zenger, Lindsay C. Rupp, Akil Narayan, Jess D. Tate, Rob S. MacLeod
2021	—	`conf`	Uncertainty Quantification of the Effects of Segmentation Variability in ECGI. FIMH Jess D. Tate, Wilson W. Good, Nejib Zemzemi, Machteld J. Boonstra, Peter M. van Dam, Dana H. Brooks, Akil Narayan, Rob S. MacLeod
2020	J	`jnl`	A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds. SIAM J. Sci. Comput. Varun Shankar, Grady B. Wright, Akil Narayan
2020	J	`jnl`	Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing. CoRR Yiming Xu, Akil Narayan, Hoang Tran, Clayton G. Webster
2020	J	`jnl`	Constructing Least-Squares Polynomial Approximations. SIAM Rev. Ling Guo, Akil Narayan, Tao Zhou
2020	J	`jnl`	Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points. CoRR Kyle M. Burk, Akil Narayan, Joseph A. Orr
2020	J	`jnl`	Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization. IEEE Trans. Smart Grid Roohallah Khatami, Masood Parvania, Akil Narayan
2020	J	`jnl`	Generation of nested quadrature rules for generic weight functions via numerical optimization: Application to sparse grids. J. Comput. Phys. Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2020	J	`jnl`	Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations. CoRR Dihan Dai, Yekaterina Epshteyn, Akil Narayan
2020	J	`jnl`	L1-based reduced over collocation and hyper reduction for steady state and time-dependent nonlinear equations. CoRR Yanlai Chen, Lijie Ji, Akil Narayan, Zhenli Xu
2020	J	`jnl`	Sparse approximation of data-driven Polynomial Chaos expansions: an induced sampling approach. CoRR Ling Guo, Akil Narayan, Yongle Liu, Tao Zhou
2020	J	`jnl`	Structure-Preserving Function Approximation via Convex Optimization. SIAM J. Sci. Comput. Vidhi Zala, Mike Kirby, Akil Narayan
2020	J	`jnl`	Structure-preserving function approximation via convex optimization. CoRR Vidhi Zala, Robert M. Kirby, Akil Narayan
2020	—	`conf`	Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations. CinC Lindsay C. Rupp, Zexin Liu, Jake A. Bergquist, Sumientra Rampersad, Dan White, Jess D. Tate, Dana H. Brooks, Akil Narayan, Rob S. MacLeod
2019	—	`conf`	A Comparison of Methods for Examining the Effect of Uncertainty in the Conductivities in a Model of Partial Thickness Ischaemia. CinC Barbara M. Johnston, Akil Narayan, Peter R. Johnston
2019	J	`jnl`	A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds. CoRR Varun Shankar, Grady B. Wright, Akil Narayan
2019	J	`jnl`	A robust error estimator and a residual-free error indicator for reduced basis methods. Comput. Math. Appl. Yanlai Chen, Jiahua Jiang, Akil Narayan
2019	J	`jnl`	Allocation Strategies for High Fidelity Models in the Multifidelity Regime. SIAM/ASA J. Uncertain. Quantification Daniel J. Perry, Robert M. Kirby, Akil Narayan, Ross T. Whitaker
2019	J	`jnl`	An efficient solver for cumulative density function-based solutions of uncertain kinematic wave models. J. Comput. Phys. Ming Cheng, Akil Narayan, Yi Qin, Peng Wang, Xinghui Zhong, Xueyu Zhu
2019	J	`jnl`	Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs. SIAM J. Sci. Comput. Roland Pulch, Akil Narayan
2019	J	`jnl`	Convergence Acceleration for Time-Dependent Parametric Multifidelity Models. SIAM J. Numer. Anal. Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2019	J	`jnl`	Data assimilation for models with parametric uncertainty. J. Comput. Phys. Lun Yang, Yi Qin, Akil Narayan, Peng Wang
2019	J	`jnl`	Fast predictive multi-fidelity prediction with models of quantized fidelity levels. J. Comput. Phys. Mani Razi, Robert M. Kirby, Akil Narayan
2019	J	`jnl`	Reduced Basis Methods for Fractional Laplace Equations via Extension. SIAM J. Sci. Comput. Harbir Antil, Yanlai Chen, Akil Narayan
2018	J	`jnl`	A gradient enhanced J. Comput. Phys. Ling Guo, Akil Narayan, Tao Zhou
2018	J	`jnl`	Allocation strategies for high fidelity models in the multifidelity regime. CoRR Daniel J. Perry, Robert M. Kirby, Akil Narayan, Ross T. Whitaker
2018	J	`jnl`	Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations. SIAM/ASA J. Uncertain. Quantification Ben Adcock, Anyi Bao, John D. Jakeman, Akil Narayan
2018	—	`conf`	Continuous-Time Stochastic Modeling and Estimation of Electricity Load. CDC Roohallah Khatami, Masood Parvania, Pramod P. Khargonekar, Akil Narayan
2018	J	`jnl`	Numerical Integration in Multiple Dimensions with Designed Quadrature. CoRR Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2018	J	`jnl`	Numerical Integration in Multiple Dimensions with Designed Quadrature. SIAM J. Sci. Comput. Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2018	J	`jnl`	Parametric Topology Optimization with Multi-Resolution Finite Element Models. CoRR Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
2018	J	`jnl`	Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction. J. Comput. Phys. Jerrad Hampton, Hillary R. Fairbanks, Akil Narayan, Alireza Doostan
2018	J	`jnl`	RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for Solving PDEs on Surfaces. CoRR Varun Shankar, Akil Narayan, Robert M. Kirby
2018	J	`jnl`	RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces. J. Comput. Phys. Varun Shankar, Akil Narayan, Robert M. Kirby
2018	J	`jnl`	Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation. SIAM J. Sci. Comput. Ling Guo, Akil Narayan, Liang Yan, Tao Zhou
2017	J	`jnl`	A Christoffel function weighted least squares algorithm for collocation approximations. Math. Comput. Akil Narayan, John D. Jakeman, Tao Zhou
2017	J	`jnl`	A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions. SIAM J. Sci. Comput. John D. Jakeman, Akil Narayan, Tao Zhou
2017	J	`jnl`	Effectively Subsampled Quadratures for Least Squares Polynomial Approximations. SIAM/ASA J. Uncertain. Quantification Pranay Seshadri, Akil Narayan, Sankaran Mahadevan
2017	J	`jnl`	Numerical Computation of Weil-Peterson Geodesics in the Universal Teichmüller Space. SIAM J. Imaging Sci. Matt Feiszli, Akil Narayan
2017	J	`jnl`	Offline-Enhanced Reduced Basis Method Through Adaptive Construction of the Surrogate Training Set. J. Sci. Comput. Jiahua Jiang, Yanlai Chen, Akil Narayan
2017	J	`jnl`	Sequential data assimilation with multiple nonlinear models and applications to subsurface flow. J. Comput. Phys. Lun Yang, Akil Narayan, Peng Wang
2017	J	`jnl`	Stochastic Collocation Methods via ℓ SIAM J. Sci. Comput. Ling Guo, Akil Narayan, Tao Zhou, Yuhang Chen
2016	J	`jnl`	A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm. SIAM/ASA J. Uncertain. Quantification Jiahua Jiang, Yanlai Chen, Akil Narayan
2016	J	`jnl`	A Reduced Radial Basis Function Method for Partial Differential Equations on Irregular Domains. J. Sci. Comput. Yanlai Chen, Sigal Gottlieb, Alfa R. H. Heryudono, Akil Narayan
2015	J	`jnl`	Weighted discrete least-squares polynomial approximation using randomized quadratures. J. Comput. Phys. Tao Zhou, Akil Narayan, Dongbin Xiu
2014	J	`jnl`	A Stochastic Collocation Algorithm with Multifidelity Models. SIAM J. Sci. Comput. Akil Narayan, Claude Jeffrey Gittelson, Dongbin Xiu
2014	J	`jnl`	Adaptive Leja Sparse Grid Constructions for Stochastic Collocation and High-Dimensional Approximation. SIAM J. Sci. Comput. Akil Narayan, John D. Jakeman
2014	J	`jnl`	Approximating the Weil-Petersson Metric Geodesics on the Universal Teichmüller Space by Singular Solutions. SIAM J. Imaging Sci. Sergey Kushnarev, Akil Narayan
2014	J	`jnl`	Computational Aspects of Stochastic Collocation with Multifidelity Models. SIAM/ASA J. Uncertain. Quantification Xueyu Zhu, Akil Narayan, Dongbin Xiu
2014	J	`jnl`	Multivariate Discrete Least-Squares Approximations with a New Type of Collocation Grid. SIAM J. Sci. Comput. Tao Zhou, Akil Narayan, Zhiqiang Xu
2013	J	`jnl`	Constructing Nested Nodal Sets for Multivariate Polynomial Interpolation. SIAM J. Sci. Comput. Akil Narayan, Dongbin Xiu
2013	J	`jnl`	Minimal multi-element stochastic collocation for uncertainty quantification of discontinuous functions. J. Comput. Phys. John D. Jakeman, Akil Narayan, Dongbin Xiu
2012	J	`jnl`	Sequential data assimilation with multiple models. J. Comput. Phys. Akil Narayan, Youssef M. Marzouk, Dongbin Xiu
2012	J	`jnl`	Stochastic Collocation Methods on Unstructured Grids in High Dimensions via Interpolation. SIAM J. Sci. Comput. Akil Narayan, Dongbin Xiu
2011	J	`jnl`	A generalization of the Wiener rational basis functions on infinite intervals: Part I-derivation and properties. Math. Comput. Akil Narayan, Jan S. Hesthaven