math.NA

Papers filed under math.NA on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

Search paper metadata (including unsummarized papers)

721 to 780 of 954

Randomized Iterative Methods for Linear Systems
Robert M. Gower, Peter Richtárik
math.NAarXiv:1506.03296v52015
A Tutorial on Inverse Problems for Anomalous Diffusion Processes
Bangti Jin, William Rundell
math.NAarXiv:1501.00251v12015
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks
Colby L. Wight, Jia Zhao
math.NAcs.NEarXiv:2007.04542v12020
Exact Support Recovery for Sparse Spikes Deconvolution
Vincent Duval, Gabriel Peyré
math.OCcs.ITmath.NAarXiv:1306.6909v32013
Kinetic energy preserving and entropy stable finite volume schemes for compressible Euler and Navier-Stokes equations
Praveen Chandrashekar
math.NAcs.CEarXiv:1209.4994v12012
Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries
Irene Vignon-Clementel, C. A. Figueroa, K. E. Jansen +1
physics.med-phmath.NAarXiv:1012.0736v12010
On the numerical approximation of the Perron-Frobenius and Koopman operator
Stefan Klus, Péter Koltai, Christof Schütte
math.DSmath.NAarXiv:1512.05997v32015
The Lyapunov Characteristic Exponents and their computation
Charalampos Skokos
nlin.CDastro-phmath-pharXiv:0811.0882v22008
Nonconvex Nonsmooth Low-Rank Minimization via Iteratively Reweighted Nuclear Norm
Canyi Lu, Jinhui Tang, Shuicheng Yan +1
cs.LGcs.CVmath.NAarXiv:1510.06895v12015
Optimization Techniques on Riemannian Manifolds
Steven Thomas Smith
math.OCcs.CGmath.DGarXiv:1407.5965v12014
Finite Element Methods for Maxwell's Equations
Peter Monk, Yangwen Zhang
math.NAarXiv:1910.10069v12019
A General Analysis of the Convergence of ADMM
Robert Nishihara, Laurent Lessard, Benjamin Recht +2
math.OCmath.NAarXiv:1502.02009v32015
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
Boris Bonev, Thorsten Kurth, Christian Hundt +4
cs.LGmath.NAphysics.ao-pharXiv:2306.03838v12023
An integral method for solving nonlinear eigenvalue problems
Wolf-Jürgen Beyn
math.NAarXiv:1003.1580v12010
Physics-informed neural networks for inverse problems in supersonic flows
Ameya D. Jagtap, Zhiping Mao, Nikolaus Adams +1
math.NAcs.LGarXiv:2202.11821v12022
Numerical Approximations for a three components Cahn-Hilliard phase-field Model based on the Invariant Energy Quadratization method
Xiaofeng Yang, Jia Zhao, Qi Wang +1
math.NAarXiv:1701.07469v12017
Solving Quadratic Equations via PhaseLift when There Are About As Many Equations As Unknowns
Emmanuel J. Candes, Xiaodong Li
cs.ITmath.NAarXiv:1208.6247v22012
NURBS-based finite element analysis of functionally graded plates: static bending, vibration, buckling and flutter
Navid Valizadeh, Sundararajan Natarajan, Octavio A Gonzalez-Estrada +3
math.NAarXiv:1210.4676v32012
Physics informed deep learning for computational elastodynamics without labeled data
Chengping Rao, Hao Sun, Yang Liu
math.NAcs.AIcs.CEarXiv:2006.08472v12020
Transolver: A Fast Transformer Solver for PDEs on General Geometries
Haixu Wu, Huakun Luo, Haowen Wang +2
cs.LGmath.NAarXiv:2402.02366v22024
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations
Bin Shi, Simon S. Du, Michael I. Jordan +1
math.OCcs.LGmath.CAarXiv:1810.08907v32018
Proximal Newton-type methods for minimizing composite functions
Jason D. Lee, Yuekai Sun, Michael A. Saunders
stat.MLcs.DScs.LGarXiv:1206.1623v132012
Convex optimization
Evgeniya Vorontsova, Roland Hildebrand, Alexander Gasnikov +1
math.OCmath.NAarXiv:2106.01946v42021
Summaries:한국어
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations
E. Kharazmi, Z. Zhang, G. E. Karniadakis
cs.NEcs.LGmath.NAarXiv:1912.00873v12019
Stable Generalized Finite Element Method (SGFEM)
I. Babuska, U. Banerjee
math.NAarXiv:1104.0960v12011
Compact difference schemes for the modified anomalous fractional sub-diffusion equation and the fractional diffusion-wave equation
Zhibo Wang, Seakweng Vong
math.NAarXiv:1310.5298v22013
A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs
Stefania Fresca, Luca Dede, Andrea Manzoni
math.NAcs.LGarXiv:2001.04001v12020
Optimal tuning of the Hybrid Monte-Carlo Algorithm
Alexandros Beskos, Natesh S. Pillai, Gareth O. Roberts +2
math.PRmath.NAarXiv:1001.4460v12010
Computing in Operations Research using Julia
Miles Lubin, Iain Dunning
math.OCcs.PLmath.NAarXiv:1312.1431v12013
Randomized Extended Kaczmarz for Solving Least-Squares
Anastasios Zouzias, Nikolaos Freris
math.NAcs.DSarXiv:1205.5770v32012
Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations
Christian Beck, Weinan E, Arnulf Jentzen
math.NAcs.LGcs.NEarXiv:1709.05963v12017
Langevin Thermostat for Rigid Body Dynamics
Ruslan L. Davidchack, Richard Handel, M. V. Tretyakov
physics.comp-phmath.NAmath.PRarXiv:0901.4725v12009
A class of asymptotic preserving schemes for kinetic equations and related problems with stiff sources
Francis Filbet, S. Jin
math.NAarXiv:0905.1378v12009
Understanding and mitigating gradient pathologies in physics-informed neural networks
Sifan Wang, Yujun Teng, Paris Perdikaris
cs.LGmath.NAstat.MLarXiv:2001.04536v12020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs
Siddhartha Mishra, Roberto Molinaro
math.NAcs.LGmath-pharXiv:2007.01138v32020
ReLU Deep Neural Networks and Linear Finite Elements
Juncai He, Lin Li, Jinchao Xu +1
math.NAarXiv:1807.03973v22018
Efficient and Modular Implicit Differentiation
Mathieu Blondel, Quentin Berthet, Marco Cuturi +5
cs.LGmath.NAstat.MLarXiv:2105.15183v52021
Synchrosqueezing-based Recovery of Instantaneous Frequency from Nonuniform Samples
Gaurav Thakur, Hau-Tieng Wu
math.NAarXiv:1006.2533v42010
High-order quantum algorithm for solving linear differential equations
Dominic W. Berry
quant-phmath.NAarXiv:1010.2745v22010
Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method
Deanna Needell, Joel A. Tropp
math.NAarXiv:1208.3805v32012
A New Selection Operator for the Discrete Empirical Interpolation Method -- improved a priori error bound and extensions
Zlatko Drmac, Serkan Gugercin
math.NAmath.DSarXiv:1505.00370v22015
An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors
Yangyang Xu, Wotao Yin, Zaiwen Wen +1
cs.ITmath.NAarXiv:1103.1168v22011
A Review of Pseudospectral Optimal Control: From Theory to Flight
I. M. Ross, M. Karpenko
math.OCcs.AIeess.SYarXiv:2511.20843v12025
An analysis of the L1 Scheme for the subdiffusion equation with nonsmooth data
Bangti Jin, Raytcho Lazarov, Zhi Zhou
math.NAarXiv:1501.00253v12015
Efficient training of physics-informed neural networks via importance sampling
Mohammad Amin Nabian, Rini Jasmine Gladstone, Hadi Meidani
cs.LGmath.APmath.NAarXiv:2104.12325v12021
Randomized Methods for Linear Constraints: Convergence Rates and Conditioning
D. Leventhal, A. S. Lewis
math.OCmath.NAarXiv:0806.3015v12008
Shifted Power Method for Computing Tensor Eigenpairs
Tamara G. Kolda, Jackson R. Mayo
math.NAarXiv:1007.1267v22010
Parallel matrix factorization for low-rank tensor completion
Yangyang Xu, Ruru Hao, Wotao Yin +1
math.NAstat.COarXiv:1312.1254v22013
Improved analysis of the subsampled randomized Hadamard transform
Joel A. Tropp
math.NAcs.DSmath.PRarXiv:1011.1595v42010
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control
Urban Fasel, J. Nathan Kutz, Bingni W. Brunton +1
math.NAmath.DSmath.OCarXiv:2111.10992v12021
Accelerated, Parallel and Proximal Coordinate Descent
Olivier Fercoq, Peter Richtárik
math.OCcs.DCmath.NAarXiv:1312.5799v22013
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning
Zhewei Yao, Amir Gholami, Sheng Shen +3
cs.LGmath.NAstat.MLarXiv:2006.00719v32020
Discretisation of heterogeneous and anisotropic diffusion problems on general non-conforming meshes. SUSHI: a scheme using stabilisation and hybrid interfaces
Robert Eymard, Thierry Gallouët, Raphaele Herbin
math.NAarXiv:0801.1430v52008
A quantum-assisted framework for PDE-based Bayesian inverse problems
Dong An, Yinan Li, Pucheng Tang +1
math.NAarXiv:2608.27028v12026
State-of-the-art SPH solver DualSPHysics: from fluid dynamics to multiphysics problems
Jose M. Domínguez, Georgios Fourtakas, Corrado Altomare +10
physics.flu-dynmath.NAarXiv:2104.00537v12021
Physics-Informed Neural Networks for Biot's Model via Fixed-Stress Splitting and Energy Natural Gradient Descent
Kexin Sun, Qiang Liu, Minfu Feng +1
math.NAmath.OCarXiv:2608.26303v12026
Stiff Norm Estimates for Variable-Stepsize Peer Two-Step Methods
Jens Lang, Bernhard A. Schmitt
math.NAarXiv:2608.26913v12026
Generalised dissipative solutions for a non-isothermal phase-field system: existence, weak-strong uniqueness, and long-time behaviour
Aaron Brunk, Marvin Fritz
math.APmath.NAarXiv:2608.26297v12026
Exact low-dimensional reformulations for regularized spectral approximation
Shengxiang Deng, Xudong Li, Yangjing Zhang
math.OCmath.NAarXiv:2608.27052v12026
Perron-Frobenius theorem for nonnegative multilinear forms and extensions
S. Friedland, S. Gaubert, L. Han
math.SPmath.NAarXiv:0905.1626v32009

math.NA

Randomized Iterative Methods for Linear Systems

A Tutorial on Inverse Problems for Anomalous Diffusion Processes

Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks

Exact Support Recovery for Sparse Spikes Deconvolution

Kinetic energy preserving and entropy stable finite volume schemes for compressible Euler and Navier-Stokes equations

Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries

On the numerical approximation of the Perron-Frobenius and Koopman operator

The Lyapunov Characteristic Exponents and their computation

Nonconvex Nonsmooth Low-Rank Minimization via Iteratively Reweighted Nuclear Norm

Optimization Techniques on Riemannian Manifolds

Finite Element Methods for Maxwell's Equations

A General Analysis of the Convergence of ADMM

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere

An integral method for solving nonlinear eigenvalue problems

Physics-informed neural networks for inverse problems in supersonic flows

Numerical Approximations for a three components Cahn-Hilliard phase-field Model based on the Invariant Energy Quadratization method

Solving Quadratic Equations via PhaseLift when There Are About As Many Equations As Unknowns

NURBS-based finite element analysis of functionally graded plates: static bending, vibration, buckling and flutter

Physics informed deep learning for computational elastodynamics without labeled data

Transolver: A Fast Transformer Solver for PDEs on General Geometries

Understanding the Acceleration Phenomenon via High-Resolution Differential Equations

Proximal Newton-type methods for minimizing composite functions

Convex optimization

Variational Physics-Informed Neural Networks For Solving Partial Differential Equations

Stable Generalized Finite Element Method (SGFEM)

Compact difference schemes for the modified anomalous fractional sub-diffusion equation and the fractional diffusion-wave equation

A comprehensive deep learning-based approach to reduced order modeling of nonlinear time-dependent parametrized PDEs

Optimal tuning of the Hybrid Monte-Carlo Algorithm

Computing in Operations Research using Julia

Randomized Extended Kaczmarz for Solving Least-Squares

Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations

Langevin Thermostat for Rigid Body Dynamics

A class of asymptotic preserving schemes for kinetic equations and related problems with stiff sources

Understanding and mitigating gradient pathologies in physics-informed neural networks

Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs

ReLU Deep Neural Networks and Linear Finite Elements

Efficient and Modular Implicit Differentiation

Synchrosqueezing-based Recovery of Instantaneous Frequency from Nonuniform Samples

High-order quantum algorithm for solving linear differential equations

Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method

A New Selection Operator for the Discrete Empirical Interpolation Method -- improved a priori error bound and extensions

An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors

A Review of Pseudospectral Optimal Control: From Theory to Flight

An analysis of the L1 Scheme for the subdiffusion equation with nonsmooth data

Efficient training of physics-informed neural networks via importance sampling

Randomized Methods for Linear Constraints: Convergence Rates and Conditioning

Shifted Power Method for Computing Tensor Eigenpairs

Parallel matrix factorization for low-rank tensor completion

Improved analysis of the subsampled randomized Hadamard transform

Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control

Accelerated, Parallel and Proximal Coordinate Descent

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Discretisation of heterogeneous and anisotropic diffusion problems on general non-conforming meshes. SUSHI: a scheme using stabilisation and hybrid interfaces

A quantum-assisted framework for PDE-based Bayesian inverse problems

State-of-the-art SPH solver DualSPHysics: from fluid dynamics to multiphysics problems

Physics-Informed Neural Networks for Biot's Model via Fixed-Stress Splitting and Energy Natural Gradient Descent

Stiff Norm Estimates for Variable-Stepsize Peer Two-Step Methods

Generalised dissipative solutions for a non-isothermal phase-field system: existence, weak-strong uniqueness, and long-time behaviour

Exact low-dimensional reformulations for regularized spectral approximation

Perron-Frobenius theorem for nonnegative multilinear forms and extensions