Jan S. Hesthaven

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 71

Top Venues

Publications

Anders Melander, Emil Strøm, Finnur Pind, Allan P. Engsig-Karup, Cheol-Ho Jeong, Tim Warburton, Noel Chalmers, Jan S. Hesthaven
Massively parallel nodal discontinous Galerkin finite element method simulator for room acoustics. Int. J. High Perform. Comput. Appl. 38 (3) (2024)
Mariella Kast, Jan S. Hesthaven
Positional embeddings for solving PDEs with evolutional deep neural networks. J. Comput. Phys. 508 (2024)
Fernando Henríquez, Jan S. Hesthaven
Fast Numerical Approximation of Linear, Second-Order Hyperbolic Problems Using Model Order Reduction and the Laplace Transform. CoRR (2024)
Philipp Weder, Mariella Kast, Fernando Henríquez, Jan S. Hesthaven
Galerkin Neural Network-POD for Acoustic and Electromagnetic Wave Propagation in Parametric Domains. CoRR (2024)
Oisín M. Morrison, Federico Pichi, Jan S. Hesthaven
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications. CoRR (2024)
Max Hirsch, Federico Pichi, Jan S. Hesthaven
Neural empirical interpolation method for nonlinear model reduction. CoRR (2024)
Nicola Rares Franco, Andrea Manzoni, Paolo Zunino, Jan S. Hesthaven
Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction. CoRR (2024)
Marco Sutti, Jan S. Hesthaven
Perfectly matched layers for the Boltzmann equation: Stability and sensitivity analysis. J. Comput. Phys. 509 (2024)
Federico Pichi, Beatriz Moya, Jan S. Hesthaven
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs. J. Comput. Phys. 501 (2024)
Junming Duan, Jan S. Hesthaven
Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems. J. Comput. Phys. 497 (2024)
Fernando Henríquez, Jan S. Hesthaven
Fast Numerical Approximation of Parabolic Problems Using Model Order Reduction and the Laplace Transform. CoRR (2024)
Marco Sutti, Jan S. Hesthaven
Perfectly matched layers for the Boltzmann equation: stability and sensitivity analysis. CoRR (2023)
Mariella Kast, Jan S. Hesthaven
Positional Embeddings for Solving PDEs with Evolutional Deep Neural Networks. CoRR (2023)
Junming Duan, Qian Wang, Jan S. Hesthaven
Machine learning enhanced real-time aerodynamic forces prediction based on sparse pressure sensor inputs. CoRR (2023)
Jan S. Hesthaven, Cecilia Pagliantini, Nicolò Ripamonti
Adaptive symplectic model order reduction of parametric particle-based Vlasov-Poisson equation. Math. Comput. 93 (347) (2023)
Federico Pichi, Beatriz Moya, Jan S. Hesthaven
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs. CoRR (2023)
Fatemeh Nassajian Mojarrad, Maria Han Veiga, Jan S. Hesthaven, Philipp Öffner
A new variable shape parameter strategy for RBF approximation using neural networks. Comput. Math. Appl. 143 (2023)
Junming Duan, Jan S. Hesthaven
Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems. CoRR (2023)
Fatemeh Nassajian Mojarrad, Maria Han Veiga, Jan S. Hesthaven, Philipp Öffner
A new variable shape parameter strategy for RBF approximation using neural networks. CoRR (2022)
Przemyslaw Zielinski, Jan S. Hesthaven
Discovery of Slow Variables in a Class Of Multiscale Stochastic Systems Via Neural Networks. J. Nonlinear Sci. 32 (4) (2022)
Paolo Conti, Mengwu Guo, Andrea Manzoni, Jan S. Hesthaven
Multi-fidelity surrogate modeling using long short-term memory networks. CoRR (2022)
Jian Yu, Jan S. Hesthaven
Model order reduction for compressible flows solved using the discontinuous Galerkin methods. J. Comput. Phys. 468 (2022)
Jan S. Hesthaven, Cecilia Pagliantini, Gianluigi Rozza
Reduced basis methods for time-dependent problems. Acta Numer. 31 (2022)
Jan S. Hesthaven, Cecilia Pagliantini, Nicolò Ripamonti
Adaptive symplectic model order reduction of parametric particle-based Vlasov-Poisson equation. CoRR (2022)
Boris Bonev, Jan S. Hesthaven
A Hierarchical Preconditioner for Wave Problems in Quasilinear Complexity. SIAM J. Sci. Comput. 44 (1) (2022)
Oscar P. Bruno, Jan S. Hesthaven, Daniel V. Leibovici
FC-based shock-dynamics solver with neural-network localized artificial-viscosity assignment. J. Comput. Phys. X 15 (2022)
Hermes Sampedro Llopis, Allan P. Engsig-Karup, Cheol-Ho Jeong, Finnur Pind, Jan S. Hesthaven
Efficient numerical room acoustic simulations with parametrized boundaries using the spectral element and reduced basis method. CoRR (2021)
Jan S. Hesthaven, Cecilia Pagliantini
Structure-preserving reduced basis methods for Poisson systems. Math. Comput. 90 (330) (2021)
Mengwu Guo, Andrea Manzoni, Maurice Amendt, Paolo Conti, Jan S. Hesthaven
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities. CoRR (2021)
Qifeng Zhang, Jan S. Hesthaven, Zhi-zhong Sun, Yunzhu Ren
Pointwise error estimate in difference setting for the two-dimensional nonlinear fractional complex Ginzburg-Landau equation. Adv. Comput. Math. 47 (3) (2021)
Federico Pichi, Francesco Ballarin, Gianluigi Rozza, Jan S. Hesthaven
An artificial neural network approach to bifurcating phenomena in computational fluid dynamics. CoRR (2021)
Jan S. Hesthaven, Fabian Mönkeberg
Hybrid high-resolution RBF-ENO method. J. Comput. Phys. X 12 (2021)
Jan S. Hesthaven, Cecilia Pagliantini, Nicolò Ripamonti
Structure-preserving model order reduction of Hamiltonian systems. CoRR (2021)
Przemyslaw Zielinski, Jan S. Hesthaven
Discovery of slow variables in a class of multiscale stochastic systems via neural networks. CoRR (2021)
Lukas Schwander, Deep Ray, Jan S. Hesthaven
Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks. J. Comput. Phys. 431 (2021)
Oscar P. Bruno, Jan S. Hesthaven, Daniel V. Leibovici
FC-based shock-dynamics solver with neural-network localized artificial-viscosity assignment. CoRR (2021)
Wenqian Chen, Qian Wang, Jan S. Hesthaven, Chuhua Zhang
Physics-informed machine learning for reduced-order modeling of nonlinear problems. J. Comput. Phys. 446 (2021)
Boris Bonev, Jan S. Hesthaven
A hierarchical preconditioner for wave problems in quasilinear complexity. CoRR (2021)
Qian Wang, Nicolò Ripamonti, Jan S. Hesthaven
Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism. J. Comput. Phys. 410 (2020)
Jim Magiera, Deep Ray, Jan S. Hesthaven, Christian Rohde
Constraint-aware neural networks for Riemann problems. J. Comput. Phys. 409 (2020)
Jan S. Hesthaven, Cecilia Pagliantini, Nicolò Ripamonti
Rank-adaptive structure-preserving reduced basis methods for Hamiltonian systems. CoRR (2020)
Jan S. Hesthaven, Fabian Mönkeberg
Two-Dimensional RBF-ENO Method on Unstructured Grids. J. Sci. Comput. 82 (3) (2020)
Niccolò Discacciati, Jan S. Hesthaven, Deep Ray
Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial viscosity tuned by neural networks. J. Comput. Phys. 409 (2020)
Wenrui Hao, Jan S. Hesthaven, Guang Lin, Bin Zheng
A Homotopy Method with Adaptive Basis Selection for Computing Multiple Solutions of Differential Equations. J. Sci. Comput. 82 (1) (2020)
Xiao Wen, Wai Sun Don, Zhen Gao, Jan S. Hesthaven
An Edge Detector Based on Artificial Neural Network with Application to Hybrid Compact-WENO Finite Difference Scheme. J. Sci. Comput. 83 (3) (2020)
Paul Cazeaux, Jan S. Hesthaven
Projective multiscale time-integration for electrostatic particle-in-cell methods. Comput. Phys. Commun. 236 (2019)
Babak Maboudi Afkham, Jan S. Hesthaven
Structure-Preserving Model-Reduction of Dissipative Hamiltonian Systems. J. Sci. Comput. 81 (1) (2019)
Ali Karakus, Noel Chalmers, Jan S. Hesthaven, Tim Warburton
Discontinuous Galerkin discretizations of the Boltzmann-BGK equations for nearly incompressible flows: Semi-analytic time stepping and absorbing boundary layers. J. Comput. Phys. 390 (2019)
Qian Wang, Jan S. Hesthaven, Deep Ray
Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem. J. Comput. Phys. 384 (2019)
Deep Ray, Jan S. Hesthaven
Detecting troubled-cells on two-dimensional unstructured grids using a neural network. J. Comput. Phys. 397 (2019)
Allan S. Nielsen, Gilles Brunner, Jan S. Hesthaven
Communication-aware adaptive Parareal with application to a nonlinear hyperbolic system of partial differential equations. J. Comput. Phys. 371 (2018)
Jan S. Hesthaven, Stefano Ubbiali
Non-intrusive reduced order modeling of nonlinear problems using neural networks. J. Comput. Phys. 363 (2018)
Deep Ray, Jan S. Hesthaven
An artificial neural network as a troubled-cell indicator. J. Comput. Phys. 367 (2018)
Boris Bonev, Jan S. Hesthaven, Francis X. Giraldo, Michal A. Kopera
Discontinuous Galerkin scheme for the spherical shallow water equations with applications to tsunami modeling and prediction. J. Comput. Phys. 362 (2018)
Babak Maboudi Afkham, Jan S. Hesthaven
Structure Preserving Model Reduction of Parametric Hamiltonian Systems. SIAM J. Sci. Comput. 39 (6) (2017)
Daniel Baffet, Jan S. Hesthaven
High-Order Accurate Local Schemes for Fractional Differential Equations. J. Sci. Comput. 70 (1) (2017)
Caterina Bigoni, Jan S. Hesthaven
Adaptive WENO Methods Based on Radial Basis Function Reconstruction. J. Sci. Comput. 72 (3) (2017)
Paolo Gatto, Jan S. Hesthaven
Efficient Preconditioning of hp-FEM Matrices by Hierarchical Low-Rank Approximations. J. Sci. Comput. 72 (1) (2017)
Daniel Baffet, Jan S. Hesthaven
A Kernel Compression Scheme for Fractional Differential Equations. SIAM J. Numer. Anal. 55 (2) (2017)
Daniel Baffet, Jan S. Hesthaven
High-Order Accurate Adaptive Kernel Compression Time-Stepping Schemes for Fractional Differential Equations. J. Sci. Comput. 72 (3) (2017)
Ulrich Rüde, Karen Willcox, Lois Curfman McInnes, Hans De Sterck, George Biros, Hans-Joachim Bungartz, James Corones, Evin Cramer, James Crowley, Omar Ghattas, Max D. Gunzburger, Michael Hanke, Robert J. Harrison, Michael A. Heroux, Jan S. Hesthaven, Peter K. Jimack, Chris Johnson, Kirk E. Jordan, David E. Keyes, Rolf H. Krause, Vipin Kumar, Stefan Mayer, Juan Meza, Knut Martin Mørken, J. Tinsley Oden, Linda R. Petzold, Padma Raghavan, Suzanne M. Shontz, Anne E. Trefethen, Peter R. Turner, Vladimir V. Voevodin, Barbara I. Wohlmuth, Carol S. Woodward
Research and Education in Computational Science and Engineering. CoRR (2016)
Jan S. Hesthaven, Shun Zhang
On the Use of ANOVA Expansions in Reduced Basis Methods for Parametric Partial Differential Equations. J. Sci. Comput. 69 (1) (2016)
Allan S. Nielsen, Jan S. Hesthaven
Fault Tolerance in the Parareal Method. FTXS@HPDC (2016)
Liangliang Qiu, Weihua Deng, Jan S. Hesthaven
Nodal discontinuous Galerkin methods for fractional diffusion equations on 2D domain with triangular meshes. J. Comput. Phys. 298 (2015)
Paolo Gatto, Jan S. Hesthaven
Numerical Approximation of the Fractional Laplacian via hp-finite Elements, with an Application to Image Denoising. J. Sci. Comput. 65 (1) (2015)
Feng Chen, Qinwu Xu, Jan S. Hesthaven
A multi-domain spectral method for time-fractional differential equations. J. Comput. Phys. 293 (2015)
George E. Karniadakis, Jan S. Hesthaven, Igor Podlubny
Special Issue on "Fractional PDEs: Theory, Numerics, and Applications". J. Comput. Phys. 293 (2015)
Jens Zudrop, Jan S. Hesthaven
Accuracy of High Order and Spectral Methods for Hyperbolic Conservation Laws with Discontinuous Solutions. SIAM J. Numer. Anal. 53 (4) (2015)
Jan S. Hesthaven, Jae-Hun Jung, Allen M. Tesdall
Hyperbolic Problems: Theory and Computation. J. Sci. Comput. 64 (3) (2015)
Jan S. Hesthaven, Shun Zhang, Xueyu Zhu
Reduced Basis Multiscale Finite Element Methods for Elliptic Problems. Multiscale Model. Simul. 13 (1) (2015)
Qinwu Xu, Jan S. Hesthaven, Feng Chen
A parareal method for time-fractional differential equations. J. Comput. Phys. 293 (2015)
Jan S. Hesthaven, Shun Zhang, Xueyu Zhu
High-Order Multiscale Finite Element Method for Elliptic Problems. Multiscale Model. Simul. 12 (2) (2014)
Jichun Li, Jan S. Hesthaven
Analysis and application of the nodal discontinuous Galerkin method for wave propagation in metamaterials. J. Comput. Phys. 258 (2014)
Qinwu Xu, Jan S. Hesthaven
Stable multi-domain spectral penalty methods for fractional partial differential equations. J. Comput. Phys. 257 (2014)
Qinwu Xu, Jan S. Hesthaven
Discontinuous Galerkin Method for Fractional Convection-Diffusion Equations. SIAM J. Numer. Anal. 52 (1) (2014)
Scott E. Field, Chad R. Galley, Jan S. Hesthaven, Jason Kaye, Manuel Tiglio
Fast prediction and evaluation of gravitational waveforms using surrogate models. CoRR (2013)
Andreas Klöckner, Timothy Warburton, Jan S. Hesthaven
Solving Wave Equations on Unstructured Geometries CoRR (2013)
Akil C. Narayan, Jan S. Hesthaven
A generalization of the Wiener rational basis functions on infinite intervals, Part II - Numerical investigation. J. Comput. Appl. Math. 237 (1) (2013)
Khosro Shahbazi, Jan S. Hesthaven, Xueyu Zhu
Multi-dimensional hybrid Fourier continuation-WENO solvers for conservation laws. J. Comput. Phys. 253 (2013)
Mahadevan Ganesh, Jan S. Hesthaven, Benjamin Stamm
A reduced basis method for electromagnetic scattering by multiple particles in three dimensions. J. Comput. Phys. 231 (23) (2012)
Andreas Klöckner, Timothy Warburton, Jan S. Hesthaven
High-Order Discontinuous Galerkin Methods by GPU Metaprogramming CoRR (2012)
Jan S. Hesthaven, Benjamin Stamm, S. Zhang
Certified Reduced Basis Method for the Electric Field Integral Equation. SIAM J. Sci. Comput. 34 (3) (2012)
Khosro Shahbazi, Nathan Albin, Oscar P. Bruno, Jan S. Hesthaven
Multi-domain Fourier-continuation/WENO hybrid solver for conservation laws. J. Comput. Phys. 230 (24) (2011)
Akil Narayan, Jan S. Hesthaven
A generalization of the Wiener rational basis functions on infinite intervals: Part I-derivation and properties. Math. Comput. 80 (275) (2011)
M. Fares, Jan S. Hesthaven, Yvon Maday, Benjamin Stamm
The reduced basis method for the electric field integral equation. J. Comput. Phys. 230 (14) (2011)
Yanlai Chen, Jan S. Hesthaven, Yvon Maday, Jerónimo Rodríguez
Certified Reduced Basis Methods and Output Bounds for the Harmonic Maxwell's Equations. SIAM J. Sci. Comput. 32 (2) (2010)
Zhen Gao, Jan S. Hesthaven
On ANOVA expansions and strategies for choosing the anchor point. Appl. Math. Comput. 217 (7) (2010)
Sehun Chun, Houssem Haddar, Jan S. Hesthaven
High-order accurate thin layer approximations for time-domain electromagnetics, Part II: Transmission layers. J. Comput. Appl. Math. 234 (8) (2010)
Sehun Chun, Jan S. Hesthaven
High-order accurate thin layer approximations for time-domain electromagnetics. Part I: General metal backed coatings. J. Comput. Appl. Math. 231 (2) (2009)
Andreas Klöckner, Tim Warburton, Jeff Bridge, Jan S. Hesthaven
Nodal discontinuous Galerkin methods on graphics processors. J. Comput. Phys. 228 (21) (2009)
G. B. Jacobs, Jan S. Hesthaven
Implicit-explicit time integration of a high-order particle-in-cell method with hyperbolic divergence cleaning. Comput. Phys. Commun. 180 (10) (2009)
Gregor Gassner, Frieder Lörcher, Claus-Dieter Munz, Jan S. Hesthaven
Polymorphic nodal elements and their application in discontinuous Galerkin methods. J. Comput. Phys. 228 (5) (2009)
Jan S. Hesthaven, Robert M. Kirby
Filtering in Legendre spectral methods. Math. Comput. 77 (263) (2008)
Alex Kanevsky, Mark H. Carpenter, David I. Gottlieb, Jan S. Hesthaven
Application of implicit-explicit high order Runge-Kutta methods to discontinuous-Galerkin schemes. J. Comput. Phys. 225 (2) (2007)
Cédric Chauvière, Jan S. Hesthaven, Laura B. Lurati
Computational Modeling of Uncertainty in Time-Domain Electromagnetics. SIAM J. Sci. Comput. 28 (2) (2006)
Saul Abarbanel, David I. Gottlieb, Jan S. Hesthaven
Non-Linear PML Equations for Time Dependent Electromagnetics in Three Dimensions. J. Sci. Comput. 28 (2-3) (2006)
G. B. Jacobs, Jan S. Hesthaven
High-order nodal discontinuous Galerkin particle-in-cell method on unstructured grids. J. Comput. Phys. 214 (1) (2006)
Alex Kanevsky, Mark H. Carpenter, Jan S. Hesthaven
Idempotent filtering in spectral and spectral element methods. J. Comput. Phys. 220 (1) (2006)
Jan S. Hesthaven, Sidi Mahmoud Kaber, Laura B. Lurati
Padé-Legendre Interpolants for Gibbs Reconstruction. J. Sci. Comput. 28 (2-3) (2006)
David I. Gottlieb, Jan S. Hesthaven, George E. Karniadakis, Chi-Wang Shu
Foreword. J. Sci. Comput. 27 (1-3) (2006)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jan S. Hesthaven