Research Interests


My research interests lie in numerical analysis, scientific computing, and approximation algorithms.



Publications:

Preprints           |           Conference Proceedings           |           Journal Publications



Preprints


Title Author arXiv / PDF
Hybrid Least Squares for Learning Functions from Highly Noisy Data Ben Adcock
Bernhard Hientzsch
Akil Narayan
Yiming Xu
A Unified Framework for Efficient Kernel and Polynomial Interpolation M. Belianovich
G. E. Fasshauer
Akil Narayan
V. Shankar
Entropy Stable Reduced Order Modeling of Nonlinear Conservation Laws Using Discontinuous Galerkin Methods Ray Qu
Akil Narayan
Jesse Chan
Optimally Balancing Exploration and Exploitation to Automate Multi-Fidelity Statistical Estimation Thomas Dixon
Alex Gorodetsky
John Jakeman
Akil Narayan
Yiming Xu
Robust Multi-Manifold Clustering via Simplex Paths Haoyu Chen
Anna Little
Akil Narayan
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation Da Long
Zhitong Xu
Guang Yang
Akil Narayan
Shandian Zhe
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning Matthew Lowery
John Turnage
Zachary Morrow
John D. Jakeman
Akil Narayan
Shandian Zhe
Varun Shankar
Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems Osman Asif Malik
Yiming Xu
Nuojin Cheng
Stephen Becker
Alireza Doostan
Akil Narayan
Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures Jarom D. Hogue
Robert M. Kirby
Akil Narayan
Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs Justin Baker
Hedi Xia
Yiwei Wang
Elena Cherkaev
Akil Narayan
Long Chen
Jack Xin
Andrea L. Bertozzi
Stanley J. Osher
Bao Wang
GP-HMAT: Scalable, \$O(N\textbackslashlog(n))\$ Gaussian Process Regression with Hierarchical Low-Rank Matrices Vahid Keshavarzzadeh
Shandian Zhe
Robert M. Kirby
Akil Narayan


Conference Proceedings


Title Author Journal DOI / arXiv
19: Uncertainty Quantification of Fibrotic Conductivity Effects on Computational Model-Derived Ablation of Atypical Left Atrial Flutter Jake Bergquist
Ben Orkild
Eric Paccione
Eugene Kwan
Brian Zenger
Bram Hunt
Kyoichiro Yazaki
Rob MacLeod
Akil Narayan
Ravi Ranjan
Computing in Cardiology Conference (CinC), 2024 2024 10.22489/CinC.2024.021
18: Application of Order and Sample Selection in Uncertainty Quantification of Cardiac Models Anna Busatto
Lindsay Rupp
Karli Gillette
Gernot Plank
Akil Narayan
Rob MacLeod
Computing in Cardiology Conference (CinC), 2024 2024 10.22489/CinC.2024.006
17: Multi-Resolution Active Learning of Fourier Neural Operators Shibo Li
Xin Yu
Wei Xing
Robert Kirby
Akil Narayan
Shandian Zhe
Proceedings of The 27th International Conference on Artificial Intelligence and Statistics pp 2440--2448 2024 10.48550/arXiv.2309.16971
16: Meta-Learning with Adjoint Methods Shibo Li
Zheng Wang
Akil Narayan
Robert Kirby
Shandian Zhe
Proceedings of the 26th International Conference on Artificial Intelligence and Statistics pp 7239--7251 2023
15: Uncertainty Quantification of the Effect of Variable Conductivity in Ventricular Fibrotic Regions on Ventricular Tachycardia Jake Bergquist
Matthias Lange
Brian Zenger
Ben Orkild
Eric Paccione
Eugene Kwan
Bram Hunt
Jiawei Dong
Rob MacLeod
Akil Narayan
Ravi Ranjan
Computing in Cardiology Conference (CinC), 2023 2023 10.22489/CinC.2023.141
14: A Grid Search of Fibrosis Thresholds for Uncertainty Quantification in Atrial Flutter Simulations Ben Orkild
Jake Bergquist
Eric Paccione
Matthias Lange
Eugene Kwan
Bram Hunt
Rob MacLeod
Akil Narayan
Ravi Ranjan
Computing in Cardiology Conference (CinC), 2023 pp 1--4 2023 10.22489/CinC.2023.348
13: Largest Angle Path Distance for Multi-Manifold Clustering Haoyu Chen
Anna Little
Akil Narayan
2023 International Conference on Sampling Theory and Applications (SampTA) pp 1--7 2023 10.1109/SampTA59647.2023.10301401
12: Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks Shibo Li
Michael Penwarden
Yiming Xu
Conor Tillinghast
Akil Narayan
Mike Kirby
Shandian Zhe
Proceedings of the 40th International Conference on Machine Learning pp 19855--19881 2023
11: Nonparametric Embeddings of Sparse High-Order Interaction Events Zheng Wang
Yiming Xu
Conor Tillinghast
Shibo Li
Akil Narayan
Shandian Zhe
Proceedings of the 39th International Conference on Machine Learning pp 23237--23253 2022
10: Bayesian Continuous-Time Tucker Decomposition Shikai Fang
Akil Narayan
Robert Kirby
Shandian Zhe
Proceedings of the 39th International Conference on Machine Learning pp 6235--6245 2022
9: Heart Position Uncertainty Quantification in the Inverse Problem of Ecgi Jake A Bergquist
Lindsay C Rupp
Anna Busatto
Ben Orkild
Brian Zenger
Wilson Good
Jaume {Coll-Font}
Akil Narayan
Jess Tate
Dana Brooks
Computing in Cardiology 2022 pp 1--4 2022 10.22489/CinC.2022.374
8: Uncertainty Quantification of Cardiac Position on Deep Graph Network ECGI Xiajun Jiang
Jess Tate
Jake Bergquist
Akil Narayan
Rob MacLeod
Linwei Wang
Computing in Cardiology 2022 2022 10.22489/CinC.2022.425
7: Uncertainty Quantification of the Effects of Segmentation Variability in ECGI Jess D. Tate
Wilson W. Good
Nejib Zemzemi
Machteld Boonstra
Peter {van Dam}
Dana H. Brooks
Akil Narayan
Rob S. MacLeod
Functional Imaging and Modeling of the Heart pp 515--522 2021 10.1007/978-3-030-78710-3_49
6: Uncertainty Quantification in Simulations of Myocardial Ischemia Jake A Bergquist
Brian Zenger
Lindsay C Rupp
Akil Narayan
Jess Tate
Rob S MacLeod
2021 Computing in Cardiology (CinC) pp 1--4 2021 10.23919/CinC53138.2021.9662837
5: The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification Lindsay C Rupp
Jake A Bergquist
Brian Zenger
Karli Gillette
Akil Narayan
Jess D Tate
Gernot Plank
Rob S MacLeod
2021 Computing in Cardiology (CinC) pp 1--4 2021 10.23919/CinC53138.2021.9662950
4: Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations Lindsay C Rupp
Zexin Liu
Jake A Bergquist
Sumientra Rampersad
Dan White
Jess D Tate
Dana H Brooks
Akil Narayan
Rob S MacLeod
2020 Computing in Cardiology pp 1--4 2020 10.22489/CinC.2020.275
3: A Comparison of Methods for Examining the Effect of Uncertainty in the Conductivities in a Model of Partial Thickness Ischaemia Barbara M Johnston
Akil Narayan
Peter R Johnston
2019 Computing in Cardiology (CinC) pp Page 1-Page 4 2019 10.23919/CinC49843.2019.9005728
2: Continuous-Time Stochastic Modeling and Estimation of Electricity Load Roohallah Khatami
Masood Parvania
Pramod Khargonekar
Akil Narayan
2018 IEEE Conference on Decision and Control (CDC) pp 3988--3993 2018 10.1109/CDC.2018.8619042
1: Sampling High Dimensional Optimal Measures Akil Narayan
11th International Conference of Numerical Analysis and Applied Mathematics 2013: ICNAAM 2013 pp 902--905 2013 10.1063/1.4825644


Journal publications


Title Author Journal DOI / arXiv
92: Conformal Finite Element Methods for Nonlinear Rosenau-Burgers-Biharmonic Models Ram Jiwari
Akil Narayan
Journal of Scientific Computing v104, pp 86 2025 10.1007/s10915-025-02997-9
91: Energy Stable and Structure-Preserving Algorithms for the Stochastic Galerkin System of 2D Shallow Water Equations Yekaterina Epshteyn
Akil Narayan
Yinqian Yu
Computer Methods in Applied Mechanics and Engineering v440, pp 117932 2025 10.1016/j.cma.2025.117932
90: Influence of Material Parameter Variability on the Predicted Coronary Artery Biomechanical Environment via Uncertainty Quantification Caleb C. Berggren
David Jiang
Y. F. Jack Wang
Jake A. Bergquist
Lindsay C. Rupp
Zexin Liu
Rob S. MacLeod
Akil Narayan
Lucas H. Timmins
Biomechanics and Modeling in Mechanobiology v23, pp 927--940 2024 10.1007/s10237-023-01814-2
89: TGPT-PINN: Nonlinear Model Reduction with Transformed GPT-PINNs Yanlai Chen
Yajie Ji
Akil Narayan
Zhenli Xu
Computer Methods in Applied Mechanics and Engineering v430, pp 117198 2024 10.1016/j.cma.2024.117198
88: Subsampling of Parametric Models with Bifidelity Boosting Nuojin Cheng
Osman Asif Malik
Yiming Xu
Stephen Becker
Alireza Doostan
Akil Narayan
SIAM/ASA Journal on Uncertainty Quantification v12, pp 213--241 2024 10.1137/22M1524989
87: Energy Stable and Structure-Preserving Schemes for the Stochastic Galerkin Shallow Water Equations Dihan Dai
Yekaterina Epshteyn
Akil Narayan
ESAIM: Mathematical Modelling and Numerical Analysis v58, pp 723--757 2024 10.1051/m2an/2024012
86: An Approximate Control Variates Approach to Multifidelity Distribution Estimation Ruijian Han
Boris Kramer
Dongjin Lee
Akil Narayan
Yiming Xu
SIAM/ASA Journal on Uncertainty Quantification v12, pp 1349--1388 2024 10.1137/23M1584307
85: Uncertainty Quantification of the Effect of Cardiac Position Variability in the Inverse Problem of Electrocardiographic Imaging Jake Aaron Bergquist
Brian Zenger
Lindsay Rupp
Anna Busatto
Jess D Tate
Dana H Brooks
Akil Narayan
Rob MacLeod
Physiological Measurement v44, 2023 10.1088/1361-6579/acfc32
84: A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs Michael Penwarden
Shandian Zhe
Akil Narayan
Robert M. Kirby
Journal of Computational Physics v477, pp 111912 2023 10.1016/j.jcp.2023.111912
83: Learning Proper Orthogonal Decomposition of Complex Dynamics Using Heavy-ball Neural ODEs Justin Baker
Elena Cherkaev
Akil Narayan
Bao Wang
Journal of Scientific Computing v95, pp 54 2023 10.1007/s10915-023-02176-8
82: Non-Dissipative and Structure-Preserving Emulators via Spherical Optimization Dihan Dai
Yekaterina Epshteyn
Akil Narayan
Information and Inference: A Journal of the IMA v12, pp 494--523 2023 10.1093/imaiai/iaac021
81: Convex Optimization-Based Structure-Preserving Filter for Multidimensional Finite Element Simulations Vidhi Zala
Akil Narayan
Robert M. Kirby
Journal of Computational Physics v492, pp 112364 2023 10.1016/j.jcp.2023.112364
80: UncertainSCI: Uncertainty Quantification for Computational Models in Biomedicine and Bioengineering Akil Narayan
Zexin Liu
Jake A. Bergquist
Chantel Charlebois
Sumientra Rampersad
Lindsay Rupp
Dana Brooks
Dan White
Jess Tate
Rob S. MacLeod
Computers in Biology and Medicine v152, pp 106407 2023 10.1016/j.compbiomed.2022.106407
79: Budget-Limited Distribution Learning in Multifidelity Problems Yiming Xu
Akil Narayan
Numerische Mathematik v153, pp 171--212 2023 10.1007/s00211-022-01337-5
78: Randomized Weakly Admissible Meshes Yiming Xu
Akil Narayan
Journal of Approximation Theory v285, pp 105835 2023 10.1016/j.jat.2022.105835
77: A Stieltjes Algorithm for Generating Multivariate Orthogonal Polynomials Zexin Liu
Akil Narayan
SIAM Journal on Scientific Computing v45, pp A1125-A1147 2023 10.1137/22M1477131
76: UncertainSCI: A Python Package for Noninvasive Parametric Uncertainty Quantification of Simulation Pipelines Jess Tate
Zexin Liu
Jake A. Bergquist
Sumientra Rampersad
Dan White
Chantel Charlebois
Lindsay Rupp
Dana H. Brooks
Rob S. MacLeod
Akil Narayan
Journal of Open Source Software v8, pp 4249 2023 10.21105/joss.04249
75: A Bandit-Learning Approach to Multifidelity Approximation Yiming Xu
Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
SIAM Journal on Scientific Computing v44, pp A150-A175 2022 10.1137/21M1408312
74: Uncertainty Quantification for Ecological Models with Random Parameters Jody R. Reimer
Frederick R. Adler
Kenneth M. Golden
Akil Narayan
Ecology Letters v25, pp 2232--2244 2022 10.1111/ele.14095
73: Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference Elizabeth Qian
Jemima M. Tabeart
Christopher Beattie
Serkan Gugercin
Jiahua Jiang
Peter R. Kramer
Akil Narayan
Journal of Scientific Computing v91, pp 29 2022 10.1007/s10915-022-01798-8
72: Multifidelity Modeling for Physics-Informed Neural Networks (PINNs) Michael Penwarden
Shandian Zhe
Akil Narayan
Robert M. Kirby
Journal of Computational Physics v451, pp 110844 2022 10.1016/j.jcp.2021.110844
71: Adaptive Density Tracking by Quadrature for Stochastic Differential Equations Ryleigh A. Moore
Akil Narayan
Applied Mathematics and Computation v431, pp 127298 2022 10.1016/j.amc.2022.127298
70: Fast Barycentric-Based Evaluation Over Spectral/Hp Elements Edward Laughton
Vidhi Zala
Akil Narayan
Robert M. Kirby
David Moxey
Journal of Scientific Computing v90, pp 78 2022 10.1007/s10915-021-01750-2
69: Variational Inference for Nonlinear Inverse Problems via Neural Net Kernels: Comparison to Bayesian Neural Networks, Application to Topology Optimization Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
Computer Methods in Applied Mechanics and Engineering v400, pp 115495 2022 10.1016/j.cma.2022.115495
68: Model Reduction for Fractional Elliptic Problems Using Kato's Formula Huy Dinh
Harbir Antil
Yanlai Chen
Elena Cherkaev
Akil Narayan
Mathematical Control & Related Fields v12, pp 115--146 2022 10.3934/mcrf.2021004
67: Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Two-Dimensional Shallow Water Equations Dihan Dai
Yekaterina Epshteyn
Akil Narayan
Journal of Computational Physics v452, pp 110901 2022 10.1016/j.jcp.2021.110901
66: Kernel Optimization for Low-Rank Multifidelity Algorithms Mani Razi
Robert Mike Kirby
Akil Narayan
International Journal for Uncertainty Quantification v11, pp 31--54 2021 10.1615/Int.J.UncertaintyQuantification.2020033212
65: On the Computation of Recurrence Coefficients for Univariate Orthogonal Polynomials Zexin Liu
Akil Narayan
Journal of Scientific Computing v88, pp 53 2021 10.1007/s10915-021-01586-w
64: Sensitivity Analysis of Random Linear Differential--Algebraic Equations Using System Norms Roland Pulch
Akil Narayan
Tatjana Stykel
Journal of Computational and Applied Mathematics v397, pp 113666 2021 10.1016/j.cam.2021.113666
63: Robust Topology Optimization with Low Rank Approximation Using Artificial Neural Networks Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
Computational Mechanics v68, pp 1297--1323 2021 10.1007/s00466-021-02069-3
62: Analysis of the Ratio of \$\textbackslashell\_1\$ and \$\textbackslashell\_2\$ Norms in Compressed Sensing Yiming Xu
Akil Narayan
Hoang Tran
Clayton G. Webster
Applied and Computational Harmonic Analysis v55, pp 486--511 2021 10.1016/j.acha.2021.06.006
61: Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
SIAM Journal on Scientific Computing v43, pp A1412-A1440 2021 10.1137/20M1333407
60: Hyperbolicity-Preserving and Well-Balanced Stochastic Galerkin Method for Shallow Water Equations Dihan Dai
Yekaterina Epshteyn
Akil Narayan
SIAM Journal on Scientific Computing v43, pp A929-A952 2021 10.1137/20M1360736
59: Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/Hp Element Methods Vidhi Zala
Robert M. Kirby
Akil Narayan
SIAM Journal on Scientific Computing v43, pp A3713-A3732 2021 10.1137/20M1337223
58: L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations Yanlai Chen
Lijie Ji
Akil Narayan
Zhenli Xu
Journal of Scientific Computing v87, pp 10 2021 10.1007/s10915-021-01416-z
57: Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization Roohallah Khatami
Masood Parvania
Akil Narayan
IEEE Transactions on Smart Grid v11, pp 644--654 2020 10.1109/TSG.2019.2927600
56: Structure-Preserving Function Approximation via Convex Optimization Vidhi Zala
Mike Kirby
Akil Narayan
SIAM Journal on Scientific Computing v42, pp A3006-A3029 2020 10.1137/19M130128X
55: Generation of Nested Quadrature Rules for Generic Weight Functions via Numerical Optimization: Application to Sparse Grids Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
Journal of Computational Physics v400, pp 108979 2020 10.1016/j.jcp.2019.108979
54: Sparse Approximation of Data-Driven Polynomial Chaos Expansions: An Induced Sampling Approach Ling Guo
Akil Narayan
Yongle Liu
Tao Zhou
Communications in Mathematical Research v36, pp 128--153 2020 10.4208/cmr.2020-0010
53: A Robust Hyperviscosity Formulation for Stable RBF-FD Discretizations of Advection-Diffusion-Reaction Equations on Manifolds Varun Shankar
Grady B. Wright
Akil Narayan
SIAM Journal on Scientific Computing v42, pp A2371-A2401 2020 10.1137/19M1288747
52: Constructing Least-Squares Polynomial Approximations Ling Guo
Akil Narayan
Tao Zhou
SIAM Review v62, pp 483--508 2020 10.1137/18M1234151
51: Force-Field Coefficient Optimization of Coarse-Grained Molecular Dynamics Models with a Small Computational Budget Mani Razi
Akil Narayan
Robert M. Kirby
Dmitry Bedrov
Computational Materials Science v176, pp 109518 2020 10.1016/j.commatsci.2020.109518
50: Stress-Based Topology Optimization under Uncertainty via Simulation-Based Gaussian Process Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
Computer Methods in Applied Mechanics and Engineering v365, pp 112992 2020 10.1016/j.cma.2020.112992
49: An Efficient Method of Calculating Composition-Dependent Inter-Diffusion Coefficients Based on Compressed Sensing Method Yi Qin
Akil Narayan
Kaiming Cheng
Peng Wang
Computational Materials Science v188, pp 110145 2020 10.1016/j.commatsci.2020.110145
48: Efficient Sampling for Polynomial Chaos-Based Uncertainty Quantification and Sensitivity Analysis Using Weighted Approximate Fekete Points Kyle M. Burk
Akil Narayan
Joseph A. Orr
International Journal for Numerical Methods in Biomedical Engineering v36, pp e3395 2020 10.1002/cnm.3395
47: Optimal Design for Kernel Interpolation: Applications to Uncertainty Quantification Akil Narayan
Liang Yan
Tao Zhou
Journal of Computational Physics v430, pp 110094 2020 10.1016/j.jcp.2020.110094
46: Sensitivity Analysis of Random Linear Dynamical Systems Using Quadratic Outputs Roland Pulch
Akil Narayan
Journal of Computational and Applied Mathematics v387, pp 112491 2019 10.1016/j.cam.2019.112491
45: A Robust Error Estimator and a Residual-Free Error Indicator for Reduced Basis Methods Yanlai Chen
Jiahua Jiang
Akil Narayan
Computers & Mathematics with Applications v77, pp 1963--1979 2019 10.1016/j.camwa.2018.11.032
44: An Efficient Solver for Cumulative Density Function-Based Solutions of Uncertain Kinematic Wave Models Ming Cheng
Akil Narayan
Yi Qin
Peng Wang
Xinghui Zhong
Xueyu Zhu
Journal of Computational Physics v382, pp 138--151 2019 10.1016/j.jcp.2019.01.008
43: Parametric Topology Optimization with Multiresolution Finite Element Models Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
International Journal for Numerical Methods in Engineering v119, pp 567--589 2019 10.1002/nme.6063
42: Polynomial Chaos Expansions for Dependent Random Variables John D. Jakeman
Fabian Franzelin
Akil Narayan
Michael Eldred
Dirk Plf{\"u}ger
Computer Methods in Applied Mechanics and Engineering v351, pp 643--666 2019 10.1016/j.cma.2019.03.049
41: Reduced Basis Methods for Fractional Laplace Equations via Extension Harbir Antil
Yanlai Chen
Akil Narayan
SIAM Journal on Scientific Computing v41, pp A3552-A3575 2019 10.1137/18M1204802
40: Data Assimilation for Models with Parametric Uncertainty Lun Yang
Yi Qin
Akil Narayan
Peng Wang
Journal of Computational Physics v396, pp 785--798 2019 10.1016/j.jcp.2019.07.020
39: Fast Predictive Multi-Fidelity Prediction with Models of Quantized Fidelity Levels Mani Razi
Robert M. Kirby
Akil Narayan
Journal of Computational Physics v376, pp 992--1008 2019 10.1016/j.jcp.2018.10.025
38: Allocation Strategies for High Fidelity Models in the Multifidelity Regime Daniel J. Perry
Robert M. Kirby
Akil Narayan
Ross T. Whitaker
SIAM/ASA Journal on Uncertainty Quantification v7, pp 203--231 2019 10.1137/17M1144714
37: Balanced Truncation for Model Order Reduction of Linear Dynamical Systems with Quadratic Outputs Roland Pulch
Akil Narayan
SIAM Journal on Scientific Computing v41, pp A2270-A2295 2019 10.1137/17M1148797
36: An Error Bound for the Standard Deviation in Model Order Reduction of Linear Stochastic Galerkin Systems Roland Pulch
Akil Narayan
Proceedings in Applied Mathematics and Mechanics v19, pp e201900028 2019 10.1002/pamm.201900028
35: Convergence Acceleration for Time-Dependent Parametric Multifidelity Models V. Keshavarzzadeh
R. Kirby
A. Narayan
SIAM Journal on Numerical Analysis v57, pp 1344--1368 2019 10.1137/18M1170339
34: Computation of induced orthogonal polynomial distributions Akil Narayan
Electronic Transactions on Numerical Analysis v50, pp 71--97 2018 10.1553/etna_vol50s71
33: Numerical Integration in Multiple Dimensions with Designed Quadrature Vahid Keshavarzzadeh
Robert M. Kirby
Akil Narayan
SIAM Journal on Scientific Computing v40, pp A2033-A2061 2018 10.1137/17M1137875
32: Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations Ben Adcock
Anyi Bao
John D. Jakeman
Akil Narayan
SIAM/ASA Journal on Uncertainty Quantification v6, pp 1424--1453 2018 10.1137/17M112590X
31: Generation and Application of Multivariate Polynomial Quadrature Rules John D. Jakeman
Akil Narayan
Computer Methods in Applied Mechanics and Engineering v338, pp 134--161 2018 10.1016/j.cma.2018.04.009
30: Fast Predictive Models Based on Multi-Fidelity Sampling of Properties in Molecular Dynamics Simulations Mani Razi
Akil Narayan
Robert M. Kirby
Dmitry Bedrov
Computational Materials Science v152, pp 125--133 2018 10.1016/j.commatsci.2018.05.029
29: Practical Error Bounds for a Non-Intrusive Bi-Fidelity Approach to Parametric/Stochastic Model Reduction Jerrad Hampton
Hillary R. Fairbanks
Akil Narayan
Alireza Doostan
Journal of Computational Physics v368, pp 315--332 2018 10.1016/j.jcp.2018.04.015
28: Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation Ling Guo
Akil Narayan
Liang Yan
Tao Zhou
SIAM Journal on Scientific Computing v40, pp A366-A387 2018 10.1137/17M1140960
27: A Gradient Enhanced \$\textbackslashell\_1\$-Minimization for Sparse Approximation of Polynomial Chaos Expansions Ling Guo
Akil Narayan
Tao Zhou
Journal of Computational Physics v367, pp 49--64 2018 10.1016/j.jcp.2018.04.026
26: RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for Solving PDEs on Surfaces Varun Shankar
Akil Narayan
Robert M. Kirby
Journal of Computational Physics v373, pp 722--735 2018 10.1016/j.jcp.2018.07.015
25: Effectively Subsampled Quadratures for Least Squares Polynomial Approximations Pranay Seshadri
Akil Narayan
Sankaran Mahadevan
SIAM/ASA Journal on Uncertainty Quantification v5, pp 1003--1023 2017 10.1137/16M1057668
24: An Orthogonality Property of the Legendre Polynomials Len Bos
Akil Narayan
Norman Levenberg
Federico Piazzon
Constructive Approximation v45, pp 65--81 2017 10.1007/s00365-015-9321-3
23: Numerical Computation of Weil--Peterson Geodesics in the Universal Teichm\"uller Space Matt Feiszli
Akil Narayan
SIAM Journal on Imaging Sciences v10, pp 1322--1345 2017 10.1137/15M1043947
22: Stochastic Collocation Methods via L1 Minimization Using Randomized Quadratures Ling Guo
Akil Narayan
Tao Zhou
Yuhang Chen
SIAM Journal on Scientific Computing v39, pp A333-A359 2017 10.1137/16M1059680
21: Sequential Data Assimilation with Multiple Nonlinear Models and Applications to Subsurface Flow Lun Yang
Akil Narayan
Peng Wang
Journal of Computational Physics v346, pp 356--368 2017 10.1016/j.jcp.2017.06.026
20: A Christoffel Function Weighted Least Squares Algorithm for Collocation Approximations Akil Narayan
John Jakeman
Tao Zhou
Mathematics of Computation v86, pp 1913--1947 2017 10.1090/mcom/3192
19: A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions John Jakeman
Akil Narayan
Tao Zhou
SIAM Journal on Scientific Computing v39, pp A1114-A1144 2017 10.1137/16M1063885
18: Offline-Enhanced Reduced Basis Method Through Adaptive Construction of the Surrogate Training Set Jiahua Jiang
Yanlai Chen
Akil Narayan
Journal of Scientific Computing v73, pp 853--875 2017 10.1007/s10915-017-0551-3
17: A Goal-Oriented Reduced Basis Methods-Accelerated Generalized Polynomial Chaos Algorithm Jiang Jiang
Yanlai Chen
Akil Narayan
SIAM/ASA Journal on Uncertainty Quantification v4, pp 1398--1420 2016 10.1137/16M1055736
16: A Reduced Radial Basis Function Method for Partial Differential Equations on Irregular Domains Yanlai Chen
Sigal Gottlieb
Alfa Heryudono
Akil Narayan
Journal of Scientific Computing v66, pp 67--90 2015 10.1007/s10915-015-0013-8
15: Weighted Discrete Least-Squares Polynomial Approximation Using Randomized Quadratures Tao Zhou
Akil Narayan
Dongbin Xiu
Journal of Computational Physics v298, pp 787--800 2015 10.1016/j.jcp.2015.06.042
14: Stochastic Collocation on Unstructured Multivariate Meshes Akil Narayan
Tao Zhou
Communications in Computational Physics v18, pp 1--36 2015 10.4208/cicp.020215.070515a
13: Approximating the Weil--Petersson Metric Geodesics on the Universal Teichm\"uller Space by Singular Solutions Sergey Kushnarev
Akil Narayan
SIAM Journal on Imaging Sciences v7, pp 900--923 2014 10.1137/120898565
12: Adaptive Leja Sparse Grid Constructions for Stochastic Collocation and High-Dimensional Approximation Akil Narayan
John Jakeman
SIAM Journal on Scientific Computing v36, pp A2952-A2983 2014 10.1137/140966368
11: A Stochastic Collocation Algorithm with Multifidelity Models Akil Narayan
Claude Gittelson
Dongbin Xiu
SIAM Journal on Scientific Computing v36, pp A495-A521 2014 10.1137/130929461
10: Computational Aspects of Stochastic Collocation with Multifidelity Models Xueyu Zhu
Akil Narayan
Dongbin Xiu
SIAM/ASA Journal on Uncertainty Quantification v2, pp 444--463 2014 10.1137/130949154
9: Multivariate Discrete Least-Squares Approximations with a New Type of Collocation Grid Tao Zhou
Akil Narayan
Zhiqiang Xu
SIAM Journal on Scientific Computing v36, pp A2401-A2422 2014 10.1137/130950434
8: Minimal Multi-Element Stochastic Collocation for Uncertainty Quantification of Discontinuous Functions John D. Jakeman
Akil Narayan
Dongbin Xiu
Journal of Computational Physics v242, pp 790--808 2013 10.1016/j.jcp.2013.02.035
7: A Generalization of the Wiener Rational Basis Functions on Infinite Intervals. Part II --- Numerical Investigation Akil C. Narayan
Jan S. Hesthaven
Journal of Computational and Applied Mathematics v237, pp 18--34 2013 10.1016/j.cam.2012.06.036
6: Constructing Nested Nodal Sets for Multivariate Polynomial Interpolation Akil Narayan
Dongbin Xiu
SIAM Journal on Scientific Computing v35, pp A2293-A2315 2013 10.1137/12089613X
5: Stochastic Collocation Methods on Unstructured Grids in High Dimensions via Interpolation Akil Narayan
Dongbin Xiu
SIAM Journal on Scientific Computing v34, pp A1729-A1752 2012 10.1137/110854059
4: Computation of Connection Coefficients and Measure Modifications for Orthogonal Polynomials Akil Narayan
Jan Hesthaven
BIT Numerical Mathematics v52, pp 457--483 2012 10.1007/s10543-011-0363-z
3: Sequential Data Assimilation with Multiple Models Akil Narayan
Youssef Marzouk
Dongbin Xiu
Journal of Computational Physics v231, pp 6401--6418 2012 10.1016/j.jcp.2012.06.002
2: Distributional Sensitivity for Uncertainty Quantification Akil Narayan
Dongbin Xiu
Communications in Computational Physics v10, pp 140--160 2011 10.4208/cicp.160210.300710a
1: A Generalization of the Wiener Rational Basis Functions on Infinite Intervals: Part I--Derivation and Properties Akil C. Narayan
Jan S. Hesthaven
Mathematics of Computation v80, pp 1557--1583 2011 10.1090/S0025-5718-2010-02437-8


Unrefereed proceedings and reports


Title Author Journal DOI / arXiv
Postdoctoral Needs and Concerns: Purdue University and Beyond Akil Narayan
Nicole Weber
Peter Richtsmeier
Valentina Trinetta
David Nelson
The POSTDOCket v10, pp 5--6 2012
A Generalization of the Wiener Rational Basis Functions on Infinite Intervals Akil Narayan
PhD Thesis, Brown University 2009
Deterministic Numerical Schemes for the Boltzmann Equation Akil Narayan
Andreas Kl{\"o}ckner
2009