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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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361 to 420 of 952

  1. A Method for Representing Periodic Functions and Enforcing Exactly Periodic Boundary Conditions with Deep Neural Networks

    Suchuan Dong, Naxian Ni

    physics.comp-phcs.LGmath.NAarXiv:2007.07442v12020

  2. Unexpected Improvements to Expected Improvement for Bayesian Optimization

    Sebastian Ament, Samuel Daulton, David Eriksson +2

    cs.LGmath.NAstat.MLarXiv:2310.20708v32023
    Summaries:한국어

  3. Tensor Decomposition for Signal Processing and Machine Learning

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

    stat.MLcs.LGmath.NAarXiv:1607.01668v22016

  4. Reference-free logged energy-oracle recovery for neural approximations of symmetric coercive variational problems: conforming Riesz reconstruction and archive-level selection

    Karim Bounja, Lahcen Laayouni, Boujemaa Achchab +1

    cs.LGmath.NAarXiv:2608.16473v12026

  5. Asymptotics-guided learning and symbolic regression for dispersive resonances

    Konstantinos Alexopoulos, Josselin Garnier

    math.NAcs.LGmath-pharXiv:2608.16152v12026

  6. Generalized Multiscale Finite Element Methods (GMsFEM)

    Yalchin Efendiev, Juan Galvis, Thomas Y. Hou

    math.NAcs.CEmath.AParXiv:1301.2866v22013

  7. Quantum spectral methods for differential equations

    Andrew M. Childs, Jin-Peng Liu

    quant-phmath.NAarXiv:1901.00961v12019

  8. Semi-discrete quadratic Wasserstein energy and state-dependent Langevin exploration

    Ran Gu, Gaoyue Guo, Kelvin Shuangjian Zhang

    math.NAmath.OCmath.PRarXiv:2609.03405v12026

  9. Explicit domain preserving numerical schemes for a class of stochastic differential equations

    Charles-Edouard Bréhier, David Cohen

    math.NAmath.PRarXiv:2608.25685v12026

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

    Sinan Wang, Ruicheng Wang, Taiyuan Zhang +5

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

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

    Samuel Lanthaler, Siddhartha Mishra, George Em Karniadakis

    math.NAarXiv:2102.09618v32021

  12. Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

    Kookjin Lee, Kevin Carlberg

    math.NAarXiv:1812.08373v32018

  13. Convex Optimization: Algorithms and Complexity

    Sébastien Bubeck

    math.OCcs.CCcs.LGarXiv:1405.4980v22014

  14. Unified Form Language: A domain-specific language for weak formulations of partial differential equations

    Martin S. Alnaes, Anders Logg, Kristian B. Oelgaard +2

    cs.MScs.SCmath.NAarXiv:1211.4047v22012

  15. Spectral Convergence of Random Feature Method in Multiple Dimensions

    Pingbing Ming, Hao Yu

    math.NAcs.AIcs.LGarXiv:2609.03401v12026

  16. Constrained minimax approximation for quantum signal processing

    Yulong Dong, James B. Larsen, Lin Lin +1

    quant-phmath.NAarXiv:2608.30937v12026

  17. Nechvile-Transformed Spacecraft Dynamics and Propellant Computation in the 3-Body Problem

    Michael J. Dixon, Isaac M. Ross

    math.OCeess.SYmath.NAarXiv:2608.29271v12026

  18. Analysis of a first-order explicit positivity preserving scheme for a class of scalar SDEs

    Charles-Edouard Bréhier, David Cohen

    math.NAmath.PRarXiv:2608.25689v12026

  19. Two-level domain-decomposition AdaGrad method for scalable training of graph neural networks

    Laurynas Varnas, Julien Herrmann, Alexander Heinlein +2

    math.NAcs.LGarXiv:2608.22575v12026

  20. Shared Physics Responses Recover Hidden Rankings in Neural Operator Libraries

    Hanbing Liang, Fujun Liu

    cs.LGmath.NAphysics.comp-pharXiv:2608.20441v12026

  21. Latent-Space No-Arbitrage Geometry of Generative Models for Implied Volatility Surfaces

    Jing Wang, Shuaiqiang Liu, Cornelis Vuik

    q-fin.CPcs.AIcs.LGarXiv:2609.00332v12026

  22. Ground state preparation and energy estimation on early fault-tolerant quantum computers via quantum eigenvalue transformation of unitary matrices

    Yulong Dong, Lin Lin, Yu Tong

    quant-phmath.NAphysics.comp-pharXiv:2204.05955v22022

  23. Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

    Salvatore Cuomo, Vincenzo Schiano di Cola, Fabio Giampaolo +3

    cs.LGcs.AImath.NAarXiv:2201.05624v42022

  24. On universal approximation and error bounds for Fourier Neural Operators

    Nikola Kovachki, Samuel Lanthaler, Siddhartha Mishra

    math.NAarXiv:2107.07562v12021

  25. Randomized Numerical Linear Algebra: Foundations & Algorithms

    Per-Gunnar Martinsson, Joel Tropp

    math.NAarXiv:2002.01387v32020

  26. Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning

    Zhouchen Lin, Risheng Liu, Huan Li

    math.NAcs.LGmath.OCarXiv:1310.5035v22013

  27. Error analysis of the L1 method on graded and uniform meshes for a fractional-derivative problem in two and three dimensions

    Natalia Kopteva

    math.NAarXiv:1709.09136v62017

  28. Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

    Weinan E, Jiequn Han, Arnulf Jentzen

    math.NAcs.LGcs.NEarXiv:1706.04702v12017

  29. A decentralized proximal-gradient method with network independent step-sizes and separated convergence rates

    Zhi Li, Wei Shi, Ming Yan

    math.OCcs.DCcs.LGarXiv:1704.07807v22017

  30. Stochastic Optimization for Large-scale Optimal Transport

    Genevay Aude, Marco Cuturi, Gabriel Peyré +1

    math.OCcs.LGmath.NAarXiv:1605.08527v12016

  31. Probabilistic Numerics and Uncertainty in Computations

    Philipp Hennig, Michael A Osborne, Mark Girolami

    math.NAcs.AIcs.LGarXiv:1506.01326v12015

  32. Exact tensor completion using t-SVD

    Zemin Zhang, Shuchin Aeron

    cs.LGmath.NAstat.MLarXiv:1502.04689v22015

  33. Error Analysis of the Inverse Conductivity Problem with Scattered Measurements

    Bangti Jin, Qimeng Quan, Wenlong Zhang

    math.NAarXiv:2608.25749v12026

  34. DC approximation approaches for sparse optimization

    Hoai An Le Thi, Tao Pham Dinh, Hoai Minh Le +1

    math.NAcs.LGstat.MLarXiv:1407.0286v22014

  35. The nonconforming virtual element method

    B. Ayuso de Dios, K. Lipnikov, G. Manzini

    math.NAarXiv:1405.3741v22014

  36. Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization

    Xiao Wang, Shiqian Ma, Donald Goldfarb +1

    math.OCcs.LGmath.NAarXiv:1607.01231v42016

  37. When and why PINNs fail to train: A neural tangent kernel perspective

    Sifan Wang, Xinling Yu, Paris Perdikaris

    cs.LGmath.NAstat.MLarXiv:2007.14527v12020

  38. Tighter Theory for Local SGD on Identical and Heterogeneous Data

    Ahmed Khaled, Konstantin Mishchenko, Peter Richtárik

    cs.LGcs.DCmath.NAarXiv:1909.04746v42019

  39. Isogeometric analysis: an overview and computer implementation aspects

    Vinh Phu Nguyen, Stéphane P. A. Bordas, Timon Rabczuk

    math.NAcs.MSarXiv:1205.2129v22012

  40. Benchmarks for single-phase flow in fractured porous media

    Bernd Flemisch, Inga Berre, Wietse Boon +5

    math.NAcs.CEarXiv:1701.01496v12017

  41. Reduced Basis Methods: Success, Limitations and Future Challenges

    Mario Ohlberger, Stephan Rave

    math.NAarXiv:1511.02021v22015

  42. Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization

    Xiangru Lian, Yijun Huang, Yuncheng Li +1

    math.OCmath.NAstat.MLarXiv:1506.08272v52015

  43. Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm

    Deanna Needell, Nathan Srebro, Rachel Ward

    math.NAcs.CVcs.LGarXiv:1310.5715v52013

  44. Tensor decompositions for learning latent variable models

    Anima Anandkumar, Rong Ge, Daniel Hsu +2

    cs.LGmath.NAstat.MLarXiv:1210.7559v42012

  45. Towards a Mathematical Theory of Super-Resolution

    Emmanuel Candes, Carlos Fernandez-Granda

    cs.ITmath.NAarXiv:1203.5871v32012

  46. Phase Retrieval via Matrix Completion

    Emmanuel J. Candes, Yonina Eldar, Thomas Strohmer +1

    cs.ITmath.NAarXiv:1109.0573v22011

  47. Recovering low-rank matrices from few coefficients in any basis

    David Gross

    cs.ITmath.NAquant-pharXiv:0910.1879v52009

  48. Strong and weak divergence in finite time of Euler's method for stochastic differential equations with non-globally Lipschitz continuous coefficients

    Martin Hutzenthaler, Arnulf Jentzen, Peter E. Kloeden

    math.NAmath.PRarXiv:0905.0273v32009

  49. Magnetic Field Conforming Multiscale Formulations for Locally-Confined Nonlinear Eddy Current Problems Using the FE-HMM Method

    Innocent Niyonzima, Gérard Meunier, Antoine Marteau +4

    math.NAarXiv:2608.30542v12026

  50. Loss Landscape Features That Make Adam Stall: Definitions, Estimators, and the Preconditioned Hessian View

    Rodion Podorozhny

    cs.LGmath.NAarXiv:2608.22145v12026

  51. Detecting and Discriminating Operator Misspecification in Hybrid PDE-Parameter Learning: a Reference-Free Instrument, with Discrimination Bounded In Sample

    Eric Fock

    cs.LGmath.NAstat.MEarXiv:2608.16925v12026

  52. Beyond Field Accuracy: Two-Axis Diagnosis of Inverse-PINN Parameter Error

    Yifan Zhang, Qian Tao

    cs.LGmath.NAarXiv:2608.15373v12026

  53. Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications

    Zhongkai Hao, Songming Liu, Yichi Zhang +4

    cs.LGcs.AIcs.CVarXiv:2211.08064v22022

  54. Positivity loss in bandlimited spectral reproduction on spheres

    Hao-Ning Wu

    math.NAmath.CAarXiv:2609.02695v12026

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

    Michael Emmerich, André Deutz

    math.OCmath.NAarXiv:2407.00359v62024

  56. Deep Network Approximation Characterized by Number of Neurons

    Zuowei Shen, Haizhao Yang, Shijun Zhang

    math.NAcs.LGarXiv:1906.05497v52019

  57. A discrete Grönwall inequality with application to numerical schemes for subdiffusion problems

    Hong-lin Liao, William McLean, Jiwei Zhang

    math.NAarXiv:1803.09879v32018

  58. What Is the Fractional Laplacian?

    Anna Lischke, Guofei Pang, Mamikon Gulian +8

    math.NAarXiv:1801.09767v32018

  59. Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

    Maziar Raissi, Paris Perdikaris, George Em Karniadakis

    cs.AIcs.LGmath.DSarXiv:1711.10561v12017

  60. Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives

    A. Cichocki, A-H. Phan, Q. Zhao +4

    math.NAcs.LGarXiv:1708.09165v12017