Cover Image

Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alger, Nick, Hartland, Tucker, Petra, Noemi, Ghattas, Omar
Format:	Preprint
Published:	2023
Subjects:	Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Accelerating seismic inversion and uncertainty quantification with efficient high-rank Hessian approximations
by: Hu, Mathew, et al.
Published: (2025)

Tucker Tensor Train Taylor Series
by: Alger, Nick, et al.
Published: (2026)

A Scalable Interior-Point Gauss-Newton Method for PDE-Constrained Optimization with Bound Constraints
by: Hartland, Tucker, et al.
Published: (2024)

Low-rank approximation of analytic kernels
by: Webb, Marcus
Published: (2025)

Parametric kernel low-rank approximations using tensor train decomposition
by: Khan, Abraham, et al.
Published: (2024)

Goal-Oriented Real-Time Bayesian Inference for Linear Autonomous Dynamical Systems With Application to Digital Twins for Tsunami Early Warning
by: Henneking, Stefan, et al.
Published: (2025)

Dimension reduction for derivative-informed operator learning: An analysis of approximation errors
by: Luo, Dingcheng, et al.
Published: (2025)

Accelerated decomposition of bistochastic kernel matrices by low rank approximation
by: Vales, Chris, et al.
Published: (2025)

A polarization tensor approximation for the Hessian in iterative solvers for non-linear inverse problems
by: Watson, F. M., et al.
Published: (2021)

Fast And Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices With Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems
by: Venkat, Sreeram, et al.
Published: (2024)

Real-time aerodynamic load estimation for hypersonics via strain-based inverse maps
by: Pham, Julie, et al.
Published: (2024)

Hyperbolic trigonometric functions as approximation kernels and their properties I: generalised Fourier transforms
by: Buhmann, Martin, et al.
Published: (2025)

General superconvergence for kernel-based approximation
by: Karvonen, Toni, et al.
Published: (2025)

A First Course in Monte Carlo Methods
by: Sanz-Alonso, Daniel, et al.
Published: (2024)

Quaternion tensor low rank Quaternion tensor low-rank approximation using a family of non-convex norms
by: Zahir, Alaeddine, et al.
Published: (2024)

Time integration of quantized tensor trains using the interpolative dynamical low-rank approximation
by: Ye, Erika, et al.
Published: (2025)

Weighted balanced truncation method for approximating kernel functions by exponentials
by: Lin, Yuanshen, et al.
Published: (2025)

Boundary corrections for kernel approximation to differential operators
by: Christlieb, Andrew, et al.
Published: (2024)

A Constrained Multi-Fidelity Bayesian Optimization Method
by: Wang, Jingyi, et al.
Published: (2025)

Limits of non-local approximations to the Eikonal equation on manifolds
by: Fadili, Jalal M., et al.
Published: (2024)

Sharp inverse statements for kernel approximation: Superconvergence and saturation
by: Wenzel, Tizian
Published: (2026)

Low-rank cross approximation of function-valued tensors for reduced-order modeling of parametric PDEs
by: Budzinskiy, Stanislav, et al.
Published: (2025)

Fredholm integral equations for function approximation and the training of neural networks
by: Gelß, Patrick, et al.
Published: (2023)

Low-rank and sparse approximations for contact mechanics
by: Kollepara, Kiran Sagar
Published: (2024)

Computation of highly oscillatory integrals using a Fourier extension approximation
by: Anand, Akash, et al.
Published: (2024)

Deep neural network approximation theory for high-dimensional functions
by: Beneventano, Pierfrancesco, et al.
Published: (2021)

Non-Asymptotic Analysis of Ensemble Kalman Updates: Effective Dimension and Localization
by: Ghattas, Omar Al, et al.
Published: (2022)

Construction of high-order conservative basis-update and Galerkin dynamical low-rank integrators
by: Einkemmer, Lukas, et al.
Published: (2023)

Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems
by: Cao, Lianghao, et al.
Published: (2024)

Randomized low-rank approximation of parameter-dependent matrices
by: Kressner, Daniel, et al.
Published: (2023)

Multilevel lattice-based kernel approximation for elliptic PDEs with random coefficients
by: Gilbert, Alexander D., et al.
Published: (2025)

Point collocation with mollified piecewise polynomial approximants for high-order partial differential equations
by: Alfarisy, Dewangga, et al.
Published: (2024)

Randomized strong rank-revealing QR for column subset selection and low-rank matrix approximation
by: Grigori, Laura, et al.
Published: (2025)

General transformation neural networks: A class of parametrized functions for high-dimensional function approximation
by: Wang, Xiaoyang, et al.
Published: (2025)

Anisotropic approximation on space-time domains
by: Morin, Pedro, et al.
Published: (2025)

Inference of Heterogeneous Material Properties via Infinite-Dimensional Integrated DIC
by: Kirchhoff, Joseph, et al.
Published: (2024)

Matrices over a Hilbert space and their low-rank approximation
by: Budzinskiy, Stanislav
Published: (2025)

Dynamical low-rank approximation for the semiclassical Schrodinger equation with uncertainties
by: Liu, Liu, et al.
Published: (2026)

Regularized dynamical parametric approximation
by: Feischl, Michael, et al.
Published: (2024)

The average condition number of most tensor rank decomposition problems is infinite
by: Beltrán, Carlos, et al.
Published: (2019)