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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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961 to 1,020 of 1,857

  1. A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent

    Eduard Gorbunov, Filip Hanzely, Peter Richtárik

    math.OCcs.LGmath.NAarXiv:1905.11261v12019

  2. Constraints Preserving Lax-Wendroff Flux Reconstruction for Relativistic Hydrodynamics with General Equations of State

    Sujoy Basak, Arpit Babbar, Harish Kumar +1

    math.NAgr-qcarXiv:2505.05128v32025

  3. Approximation of high-dimensional parametric PDEs

    Albert Cohen, Ronald Devore

    math.APmath.NAarXiv:1502.06797v22015

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

    Weifeng Liu, Brian Vinter

    cs.MScs.DCmath.NAarXiv:1503.05032v22015

  5. Symmetric tensors and symmetric tensor rank

    Pierre Comon, Gene Golub, Lek-Heng Lim +1

    math.NAmath.AGarXiv:0802.1681v22008

  6. Optimal error estimates for the half-way bounce-back lattice Boltzmann method for the Stokes equations

    Kai Koike

    math.NAmath.AParXiv:2608.27926v12026

  7. Numerical approximations of stochastic differential equations with non-globally Lipschitz continuous coefficients

    Martin Hutzenthaler, Arnulf Jentzen

    math.PRmath.NAarXiv:1203.5809v22012

  8. Deep learning observables in computational fluid dynamics

    Kjetil O. Lye, Siddhartha Mishra, Deep Ray

    physics.comp-phcs.LGmath.NAarXiv:1903.03040v22019

  9. Finite strain FFT-based non-linear solvers made simple

    T. W. J. de Geus, J. Vondrejc, J. Zeman +2

    math.NAcs.NAarXiv:1603.08893v32016

  10. Optimization Techniques on Riemannian Manifolds

    Steven Thomas Smith

    math.OCcs.CGmath.DGarXiv:1407.5965v12014

  11. Solving high-dimensional partial differential equations using deep learning

    Jiequn Han, Arnulf Jentzen, Weinan E

    math.NAcs.LGmath.OCarXiv:1707.02568v32017

  12. An adaptive multigrid solver for DPG methods with applications in linear acoustics and electromagnetics

    Socratis Petrides, Leszek Demkowicz

    math.NAcs.NAarXiv:2010.06793v12020

  13. On the Complexity Analysis of Randomized Block-Coordinate Descent Methods

    Zhaosong Lu, Lin Xiao

    math.OCcs.LGmath.NAarXiv:1305.4723v12013

  14. Error analysis of penalized $H({\rm div})$-conforming finite element methods for surface Stokes problems

    Alan Demlow, Orsan Kilicer

    math.NAcs.NAarXiv:2609.28729v12026

  15. High order biorthogonal functions for the discrete de Rham complex on simplices*

    Tim Haubold, Sven Beuchler, Joachim Schöberl

    math.NAcs.NAarXiv:2609.28345v12026

  16. Deterministic guarantees for Burer-Monteiro factorizations of smooth semidefinite programs

    Nicolas Boumal, Vladislav Voroninski, Afonso S. Bandeira

    math.OCcs.NAmath.NAarXiv:1804.02008v22018

  17. Tensor Decomposition for Signal Processing and Machine Learning

    Nicholas D. Sidiropoulos, Lieven De Lathauwer, Xiao Fu +3

    stat.MLcs.LGmath.NAarXiv:1607.01668v22016

  18. Bayesian statistical inverse problems for a coupled Fokker-Planck-Darcy system

    Grigorios A. Pavliotis, Andrew M. Stuart, Andrea Zanoni

    math.STcs.NAmath.AParXiv:2609.28242v12026

  19. Deep Autoencoder based Energy Method for the Bending, Vibration, and Buckling Analysis of Kirchhoff Plates

    Xiaoying Zhuang, Hongwei Guo, Naif Alajlan +1

    cs.LGmath.NAarXiv:2010.05698v12020

  20. A Lloyd-stabilized Voronoi particle method

    Bruno Després, Borjan Geshkovski

    math.NAcs.NAarXiv:2609.28135v12026

  21. 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

  22. Modeling cardiac muscle fibers in ventricular and atrial electrophysiology simulations

    Roberto Piersanti, Pasquale C. Africa, Marco Fedele +4

    math.NAcs.CEcs.NAarXiv:2101.10960v12021

  23. Tensor Decomposition of Transformer Key-Value Caches: Spectral Structure and Format Comparison

    Rahul Krishnan, Volker Schulz

    math.NAcs.CLcs.LGarXiv:2609.28029v12026

  24. Neural Operator: Graph Kernel Network for Partial Differential Equations

    Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli +4

    cs.LGmath.NAstat.MLarXiv:2003.03485v12020

  25. Rational neural networks

    Nicolas Boullé, Yuji Nakatsukasa, Alex Townsend

    cs.NEcs.LGcs.NAarXiv:2004.01902v22020

  26. An Accelerated Randomized Kaczmarz Algorithm

    Ji Liu, Stephen J. Wright

    math.NAcs.NAmath.OCarXiv:1310.2887v22013

  27. Stable Generalized Finite Element Method (SGFEM)

    I. Babuska, U. Banerjee

    math.NAarXiv:1104.0960v12011

  28. Convex Optimization: Algorithms and Complexity

    Sébastien Bubeck

    math.OCcs.CCcs.LGarXiv:1405.4980v22014

  29. Smaller generalization error derived for a deep residual neural network compared to shallow networks

    Aku Kammonen, Jonas Kiessling, Petr Plecháč +3

    math.NAcs.NAmath.OCarXiv:2010.01887v22020

  30. Decoupled Diffusion Sampling for Inverse Problems on Function Spaces

    Thomas Y. L. Lin, Jiachen Yao, Lufang Chiang +2

    cs.LGmath.NAarXiv:2601.23280v32026

  31. Message Passing Neural PDE Solvers

    Johannes Brandstetter, Daniel Worrall, Max Welling

    cs.LGcs.CVmath.NAarXiv:2202.03376v32022

  32. Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients

    A. L. Teckentrup, R. Scheichl, M. B. Giles +1

    math.NAarXiv:1204.3476v12012

  33. Conservative Three-Layer Schemes for Kirchhoff-Type Equations

    Felix Krumbiegel, Jemal Rogava, Andreas Rupp +1

    math.NAcs.NAarXiv:2609.27707v12026

  34. Stable time-stepping via residual minimization: finite-element and neural-network approximations for transient parabolic problems

    Judit Muñoz-Matute, Sergio Rojas

    math.NAcs.NAarXiv:2609.27548v12026

  35. Learning to Optimize Multigrid PDE Solvers

    Daniel Greenfeld, Meirav Galun, Ron Kimmel +2

    math.NAcs.LGcs.NAarXiv:1902.10248v32019

  36. Construction of arbitrary order finite element degree-of-freedom maps on polygonal and polyhedral cell meshes

    Matthew W. Scroggs, Jørgen S. Dokken, Chris N. Richardson +1

    math.NAarXiv:2102.11901v52021

  37. Physics-Informed Stochastic Configuration Machine: A Backpropagation-Free Neural Network with Fast Training for Nonlinear Differential Equations

    Yuehao Song, Zhong Chen, Lihui Cen +2

    math.NAcs.AIcs.LGarXiv:2608.26549v12026

  38. Column Subset Selection, Matrix Factorization, and Eigenvalue Optimization

    Joel A. Tropp

    math.NAcs.NAmath.FAarXiv:0806.4404v12008

  39. Relative Primal--Dual Gap Certificates for Operator-Composite Trust-Region Methods

    Harbir Antil

    math.OCcs.NAmath.AParXiv:2609.27348v12026

  40. On Tensor Completion via Nuclear Norm Minimization

    Ming Yuan, Cun-Hui Zhang

    stat.MLcs.ITmath.NAarXiv:1405.1773v12014

  41. Adaptive construction of surrogates for the Bayesian solution of inverse problems

    Jinglai Li, Youssef M. Marzouk

    stat.COcs.NAmath.NAarXiv:1309.5524v12013

  42. Stable and robust sampling strategies for compressive imaging

    Felix Krahmer, Rachel Ward

    cs.CVcs.ITmath.NAarXiv:1210.2380v32012

  43. An unconventional robust integrator for dynamical low-rank approximation

    Gianluca Ceruti, Christian Lubich

    math.NAarXiv:2010.02022v12020

  44. Phase Retrieval: Stability and Recovery Guarantees

    Yonina C. Eldar, Shahar Mendelson

    cs.ITmath.NAarXiv:1211.0872v12012

  45. 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

  46. Hamiltonian Two-Way Coupling of Nonlinear Waves and 3D Flows

    Sinan Wang, Ruicheng Wang, Taiyuan Zhang +5

    cs.GRmath.NAphysics.flu-dynarXiv:2608.25203v12026

  47. Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies

    Michael Emmerich, André Deutz

    math.OCmath.NAarXiv:2407.00359v62024

  48. A physics-informed operator regression framework for extracting data-driven continuum models

    Ravi G. Patel, Nathaniel A. Trask, Mitchell A. Wood +1

    physics.comp-phcs.LGcs.NAarXiv:2009.11992v12020

  49. Pointwise Monotonicity of the Allen--Cahn Flow and Dynamical Limitations of Energy-Stable Schemes

    Pansheng Li, Dongling Wang

    math.NAarXiv:2609.19023v12026

  50. Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations

    Liu Yang, Dongkun Zhang, George Em Karniadakis

    stat.MLcs.LGmath.AParXiv:1811.02033v12018

  51. Simulation of stochastic reaction-diffusion processes on unstructured meshes

    Stefan Engblom, Lars Ferm, Andreas Hellander +1

    math.NAarXiv:0804.3288v12008

  52. Error estimates for DeepOnets: A deep learning framework in infinite dimensions

    Samuel Lanthaler, Siddhartha Mishra, George Em Karniadakis

    math.NAarXiv:2102.09618v32021

  53. A Finite-Volume Method for Nonlinear Nonlocal Equations with a Gradient Flow Structure

    José A. Carrillo, Alina Chertock, Yanghong Huang

    math.NAarXiv:1402.4252v22014

  54. On The Convergence of Gradient Descent for Finding the Riemannian Center of Mass

    Bijan Afsari, Roberto Tron, René Vidal

    math.DGcs.CVmath.NAarXiv:1201.0925v12011

  55. 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

  56. Analysis of adaptive BDF2 scheme for diffusion equations

    Hong-lin Liao, Zhimin Zhang

    math.NAcs.NAarXiv:1912.11182v12019

  57. Super-resolution via superset selection and pruning

    Laurent Demanet, Deanna Needell, Nam Nguyen

    cs.ITcs.NAmath.ITarXiv:1302.6288v22013

  58. Convergence of Entropic Schemes for Optimal Transport and Gradient Flows

    Guillaume Carlier, Vincent Duval, Gabriel Peyré +1

    math.APmath.NAarXiv:1512.02783v22015

  59. The Little Engine that Could: Regularization by Denoising (RED)

    Yaniv Romano, Michael Elad, Peyman Milanfar

    cs.CVmath.NAarXiv:1611.02862v32016

  60. Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications

    Antonin Chambolle, Matthias J. Ehrhardt, Peter Richtárik +1

    math.OCcs.CVmath.NAarXiv:1706.04957v22017