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.

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661 to 720 of 952

NETT: Solving Inverse Problems with Deep Neural Networks
Housen Li, Johannes Schwab, Stephan Antholzer +1
math.NAcs.LGarXiv:1803.00092v32018
Splitting Methods for Convex Clustering
Eric C. Chi, Kenneth Lange
stat.MLmath.NAmath.OCarXiv:1304.0499v22013
Galerkin v. least-squares Petrov--Galerkin projection in nonlinear model reduction
Kevin Carlberg, Matthew Barone, Harbir Antil
math.NAarXiv:1504.03749v32015
Off-the-Grid Line Spectrum Denoising and Estimation with Multiple Measurement Vectors
Yuanxin Li, Yuejie Chi
cs.ITmath.NAarXiv:1408.2242v22014
Breaking the coherence barrier: A new theory for compressed sensing
Ben Adcock, Anders C. Hansen, Clarice Poon +1
cs.ITmath.NAarXiv:1302.0561v42013
A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems
Lars Ruthotto, Stanley Osher, Wuchen Li +2
cs.LGmath.NAmath.OCarXiv:1912.01825v32019
Linear convergence of iterative soft-thresholding
Kristian Bredies, Dirk A. Lorenz
math.FAmath.NAarXiv:0709.1598v42007
Robust Spectral Compressed Sensing via Structured Matrix Completion
Yuxin Chen, Yuejie Chi
cs.ITeess.SYmath.NAarXiv:1304.8126v52013
Fourier-based schemes for computing the mechanical response of composites with accurate local fields
François Willot
math.NAcond-mat.mtrl-sciarXiv:1412.8398v12014
Rational Construction of Stochastic Numerical Methods for Molecular Sampling
Benedict Leimkuhler, Charles Matthews
math.NAcond-mat.stat-mechphysics.chem-pharXiv:1203.5428v22012
Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints
I. Daubechies, M. Fornasier, I. Loris
math.NAarXiv:0706.4297v22007
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations
Liu Yang, Dongkun Zhang, George Em Karniadakis
stat.MLcs.LGmath.AParXiv:1811.02033v12018
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis
stat.MLmath.APmath.DSarXiv:1703.10230v12017
A Unified Gas Kinetic Scheme for Multi-scale and Multi-component Plasma Transport
Chang Liu, Kun Xu
physics.comp-phmath.NAphysics.plasm-pharXiv:1609.05291v22016
Split Form Nodal Discontinuous Galerkin Schemes with Summation-By-Parts Property for the Compressible Euler Equations
Gregor J. Gassner, Andrew R. Winters, David A. Kopriva
math.NAarXiv:1604.06618v32016
Data-driven computational mechanics
Trenton Kirchdoerfer, Michael Ortiz
physics.comp-phmath.NAarXiv:1510.04232v12015
A Proximal Decomposition Method for Solving Convex Variational Inverse Problems
Patrick L. Combettes, Jean-Christophe Pesquet
math.OCmath.NAarXiv:0807.2617v22008
Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks
Dongkun Zhang, Ling Guo, George Em Karniadakis
cs.LGmath.NAphysics.comp-pharXiv:1905.01205v22019
A new tool to study real dynamics: The Convergence Plane
Angel Alberto Magreñan
math.NAarXiv:1310.3986v12013
Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing
Arian Maleki, David L. Donoho
math.NAcs.ITcs.MSarXiv:0909.0777v12009
Efficient quantum algorithm for dissipative nonlinear differential equations
Jin-Peng Liu, Herman Øie Kolden, Hari K. Krovi +3
quant-phmath.NAphysics.plasm-pharXiv:2011.03185v42020
Hyperbolic Cross Approximation
Dinh Dũng, Vladimir N. Temlyakov, Tino Ullrich
math.NAarXiv:1601.03978v32016
Neural Network Approximation
Ronald DeVore, Boris Hanin, Guergana Petrova
math.NAarXiv:2012.14501v12020
ADMiRA: Atomic Decomposition for Minimum Rank Approximation
Kiryung Lee, Yoram Bresler
math.NAcs.ITarXiv:0905.0044v22009
Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent
Zeyuan Allen-Zhu, Lorenzo Orecchia
cs.DScs.LGmath.NAarXiv:1407.1537v52014
Phase-field modeling of fluid-driven dynamic cracking in porous media
Shuwei Zhou, Xiaoying Zhuang, Timon Rabczuk
math.NAcs.CEarXiv:2309.02438v12023
A fractional Laplace equation: regularity of solutions and Finite Element approximations
Gabriel Acosta, Juan Pablo Borthagaray
math.NAarXiv:1507.08970v32015
Randomized Kaczmarz solver for noisy linear systems
Deanna Needell
math.NAmath.PRarXiv:0902.0958v22009
Fast L1-Minimization Algorithms For Robust Face Recognition
Allen Y. Yang, Zihan Zhou, Arvind Ganesh +2
cs.CVmath.NAarXiv:1007.3753v42010
Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks
Sarah Jane Hamilton, Andreas Hauptmann
math.NAcs.NEmath.AParXiv:1711.03180v22017
An algorithm for the principal component analysis of large data sets
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnisky +1
stat.COmath.NAarXiv:1007.5510v22010
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco, Christopher Musco
cs.DScs.LGmath.NAarXiv:1504.05477v42015
Methods of Solving Ill-Posed Problems
Suresh B. Srinivasamurthy
math.NAarXiv:1205.5323v12012
Neural networks for topology optimization
Ivan Sosnovik, Ivan Oseledets
cs.LGmath.NAarXiv:1709.09578v12017
All-at-once Optimization for Coupled Matrix and Tensor Factorizations
Evrim Acar, Tamara G. Kolda, Daniel M. Dunlavy
math.NAphysics.data-anstat.MLarXiv:1105.3422v12011
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition
Stefania Fresca, Andrea Manzoni
math.NAcs.LGarXiv:2101.11845v12021
Stability Analysis for the Virtual Element Method
Lourenco Beirao da Veiga, Carlo Lovadina, Alessandro Russo
math.NAarXiv:1607.05988v12016
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin, Kailiang Wu, Dongbin Xiu
math.NAcs.LGcs.NEarXiv:1811.05537v12018
Deep Network Approximation for Smooth Functions
Jianfeng Lu, Zuowei Shen, Haizhao Yang +1
cs.LGmath.NAstat.MLarXiv:2001.03040v82020
A combined first and second order variational approach for image reconstruction
Konstantinos Papafitsoros, Carola-Bibiane Schönlieb
math.NAarXiv:1202.6341v22012
Structure preserving numerical methods for the Vlasov equation
Lukas Einkemmer
math.NAarXiv:1604.02616v12016
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems
Elizabeth Qian, Boris Kramer, Benjamin Peherstorfer +1
math.NAcs.LGarXiv:1912.08177v52019
A Multilevel Interacting Particle System Method for the estimation of Failure Probabilities
Rubén Aylwin, José Pinto
math.NAarXiv:2608.27275v12026
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
José M. Bioucas-Dias, Mário A. T. Figueiredo
math.OCmath.NAarXiv:0912.1845v22009
A physics-informed variational DeepONet for predicting the crack path in brittle materials
Somdatta Goswami, Minglang Yin, Yue Yu +1
cs.LGmath.NAarXiv:2108.06905v22021
New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property
Felix Krahmer, Rachel Ward
cs.ITmath.NAmath.PRarXiv:1009.0744v42010
Weak SINDy For Partial Differential Equations
Daniel A. Messenger, David M. Bortz
math.NAcs.LGstat.MLarXiv:2007.02848v32020
Approximation of high-dimensional parametric PDEs
Albert Cohen, Ronald Devore
math.APmath.NAarXiv:1502.06797v22015
On Tensors, Sparsity, and Nonnegative Factorizations
Eric C. Chi, Tamara G. Kolda
math.NAarXiv:1112.2414v32011
Inertial Douglas-Rachford splitting for monotone inclusion problems
Radu Ioan Bot, Ernö Robert Csetnek, Christopher Hendrich
math.OCmath.FAmath.NAarXiv:1403.3330v22014
PyFR: An Open Source Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures using the Flux Reconstruction Approach
Freddie D Witherden, Antony M Farrington, Peter E Vincent
physics.comp-phmath.NAarXiv:1312.1638v22013
Mixed finite element methods for linear elasticity with weakly imposed symmetry
Douglas N. Arnold, Richard S. Falk, Ragnar Winther
math.NAarXiv:math/0701506v12007
CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication
Weifeng Liu, Brian Vinter
cs.MScs.DCmath.NAarXiv:1503.05032v22015
A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization
Yin Tat Lee, Aaron Sidford, Sam Chiu-wai Wong
cs.DScs.DMmath.NAarXiv:1508.04874v22015
A fast solver for many-particle elastic scattering in layered media
Jinrui Zhang, Yixiao He, Jun lai
math.NAarXiv:2608.26875v12026
WHFast: A fast and unbiased implementation of a symplectic Wisdom-Holman integrator for long term gravitational simulations
Hanno Rein, Daniel Tamayo
astro-ph.EPastro-ph.IMmath.NAarXiv:1506.01084v12015
On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions
Francis Bach
cs.LGmath.NAstat.MLarXiv:1502.06800v22015
Iteratively re-weighted least squares minimization for sparse recovery
Ingrid Daubechies, Ronald DeVore, Massimo Fornasier +1
math.NAarXiv:0807.0575v12008
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

math.NA

NETT: Solving Inverse Problems with Deep Neural Networks

Splitting Methods for Convex Clustering

Galerkin v. least-squares Petrov--Galerkin projection in nonlinear model reduction

Off-the-Grid Line Spectrum Denoising and Estimation with Multiple Measurement Vectors

Breaking the coherence barrier: A new theory for compressed sensing

A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems

Linear convergence of iterative soft-thresholding

Robust Spectral Compressed Sensing via Structured Matrix Completion

Fourier-based schemes for computing the mechanical response of composites with accurate local fields

Rational Construction of Stochastic Numerical Methods for Molecular Sampling

Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints

Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations

A Unified Gas Kinetic Scheme for Multi-scale and Multi-component Plasma Transport

Split Form Nodal Discontinuous Galerkin Schemes with Summation-By-Parts Property for the Compressible Euler Equations

Data-driven computational mechanics

A Proximal Decomposition Method for Solving Convex Variational Inverse Problems

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

A new tool to study real dynamics: The Convergence Plane

Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing

Efficient quantum algorithm for dissipative nonlinear differential equations

Hyperbolic Cross Approximation

Neural Network Approximation

ADMiRA: Atomic Decomposition for Minimum Rank Approximation

Linear Coupling: An Ultimate Unification of Gradient and Mirror Descent

Phase-field modeling of fluid-driven dynamic cracking in porous media

A fractional Laplace equation: regularity of solutions and Finite Element approximations

Randomized Kaczmarz solver for noisy linear systems

Fast L1-Minimization Algorithms For Robust Face Recognition

Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks

An algorithm for the principal component analysis of large data sets

Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

Methods of Solving Ill-Posed Problems

Neural networks for topology optimization

All-at-once Optimization for Coupled Matrix and Tensor Factorizations

POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition

Stability Analysis for the Virtual Element Method

Data Driven Governing Equations Approximation Using Deep Neural Networks

Deep Network Approximation for Smooth Functions

A combined first and second order variational approach for image reconstruction

Structure preserving numerical methods for the Vlasov equation

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

A Multilevel Interacting Particle System Method for the estimation of Failure Probabilities

Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization

A physics-informed variational DeepONet for predicting the crack path in brittle materials

New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property

Weak SINDy For Partial Differential Equations

Approximation of high-dimensional parametric PDEs

On Tensors, Sparsity, and Nonnegative Factorizations

Inertial Douglas-Rachford splitting for monotone inclusion problems

PyFR: An Open Source Framework for Solving Advection-Diffusion Type Problems on Streaming Architectures using the Flux Reconstruction Approach

Mixed finite element methods for linear elasticity with weakly imposed symmetry

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

A Faster Cutting Plane Method and its Implications for Combinatorial and Convex Optimization

A fast solver for many-particle elastic scattering in layered media

WHFast: A fast and unbiased implementation of a symplectic Wisdom-Holman integrator for long term gravitational simulations

On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions

Iteratively re-weighted least squares minimization for sparse recovery

Randomized Iterative Methods for Linear Systems

A Tutorial on Inverse Problems for Anomalous Diffusion Processes