Neural-Network Approximation

Ask about this topic

Recent momentum

-38%

8 papers in the last 28 days · 0.1% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Also in Approximation

Neighbouring directions

ApproximationApproximation Algorithms

Weekly history

Recent digests

What was published in this topic, kept on the site without email delivery.

Period ending 2026-09-21

4 new papers

A weekly snapshot of new work published in Neural-Network Approximation.

Period ending 2026-09-07

3 new papers

A weekly snapshot of new work published in Neural-Network Approximation.

98 papers

Latest in Neural-Network Approximation

Browse all topics →
CardsList

  1. A Hybrid Iterative Deep Ritz Method for Elliptic Interface Problems

    Sep 23, 2026Tianhao Hu, Bangti Jin, Fengru Wang +1Boundary Value ProblemsNeural-Network Approximation

  2. Neural Approximation by Function Composition: Rigidity and Doubly Exponential Convergence

    Sep 22, 2026Wentao Huang, Haizhang ZhangNeural-Network Approximation

  3. Optimal Tradeoffs Between Network Size and Parameter Magnitude in Neural Approximation and Minimax Regression

    Sep 22, 2026Baicheng Li, Zuowei Shen, Haizhao Yang +1Neural-Network Approximation

  4. Beyond PINNs: A Unified Gauss--Newton and Petrov--Galerkin Framework for Neural and Hybrid PDE Solvers

    Sep 17, 2026Nilo Schwencke, Roland MaierBayesian QuadraturePartial Differential Equation Benchmarks

  5. Error bounds in Sobolev norms for approximations with norm constrained ReLU neural networks

    Sep 17, 2026Xianjun Li, Yunfei YangLogarithmic Sobolev InequalitiesRectified Linear Unit Networks

  6. Learning Lyapunov Operators for Nonlinear Systems

    Sep 16, 2026Amartya Mukherjee, Maxwell Fitzsimmons, David C. Del Rey Fernández +1Fourier Neural OperatorsLyapunov Function

  7. Approximating Smooth Functionals with ReLU Networks

    Sep 14, 2026Shuhao JiaoNeural-Network ApproximationRectified Linear Unit

  8. Residual neural networks overcome the curse of dimensionality for semilinear heat equations

    Sep 3, 2026Ilkhom Mukhammadiev, Diyora SalimovaNeural-Network ApproximationResidual Connections

  9. Sharp Approximation Rates for Neural Networks with Affine Latent Parameterizations

    Aug 31, 2026Shijun ZhangNeural-Network ApproximationApproximation

  10. Graph4BiLO: Graph Neural Network Approximation for Bilevel Mixed-Integer Linear Optimization

    Aug 31, 2026Jessica D. Elrefaei, Kaixun Hua, Seungbae Kim +2Bilevel OptimizationGraph Neural Networks

  11. Data-driven Koopman mode approximation: A neural power iteration algorithm

    Aug 27, 2026Guillaume O. Berger, Raphaël M. JungersKoopman OperatorNonlinear Dynamics

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

    Aug 17, 2026Karim Bounja, Lahcen Laayouni, Boujemaa Achchab +1Neural-Network ApproximationNeural Partial Differential Equation Solvers

  13. Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies

    Aug 11, 2026Ziqian Li, Nikolaos M. MatzakosNeural Ordinary Differential EquationsNeural-Network Approximation

  14. Walk-on-Spheres Monte Carlo and deep neural network approximations of elliptic PDEs with drift and killing

    Aug 10, 2026Konrad Kleinberg, Thomas KruseNeural-Network ApproximationStochastic Differential Equations

  15. Approximation Rates for Metaplectic Neural Networks

    Aug 9, 2026Ahmed Abdeljawad, Marcello Carioni, Elena CorderoNeural-Network ApproximationQuantum Neural Networks

  16. A cylindrical neural approximation theorem for conditional laws of McKean-Vlasov equations with common noise

    Aug 8, 2026Nacira Agram, Reda Hmioui, Jan RemsNeural-Network ApproximationFokker--Planck Equation

  17. Optimal Neural Network Approximation via Empirical Least Squares with Deterministic Samples

    Aug 7, 2026Xinliang Liu, Tong Mao, Jinchao XuNeural-Network ApproximationBayesian Quadrature

  18. Fixed and Adaptive Topological DeepONets: Functional Measurements on Hausdorff Locally Convex Spaces

    Aug 5, 2026Khemraj Shukla, George Em KarniadakisFourier Neural OperatorsShallow Water Equations

  19. PLAN: Parallel Liquid-Inspired Approximation Network for Efficient Representation Learning in Flexible Job Shop Scheduling

    Aug 4, 2026Dhivya Dharshini Kannan, Wei Zhang, Jieyi Bi +5Neural-Network ApproximationDeep Reinforcement Learning

  20. Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View

    Aug 2, 2026Tong Mao, Jinchao XuNeural-Network ApproximationApproximation

  21. Neural Network Approximation of Solutions to Fractional Parabolic Partial Differential Equations

    Jul 30, 2026Jae-Hwan Choi, Hyojae Lim, Jinsol Seo +2Neural-Network ApproximationPartial Differential Equations

  22. Error Analysis of Neural-Network-Based Engression

    Jul 30, 2026Juntong Chen, Zijian Guo, Xinwei ShenNeural-Network ApproximationConditional Distribution

  23. Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes

    Jul 29, 2026Lennon J. Shikhman, Michael Galarnyk, Aadi Dash +1Derivative PricingNeural-Network Approximation

  24. Universality and Approximation Rates of Graph Neural Networks with Random Features

    Jul 29, 2026Lukas Gonon, Thilo Meyer-Brandis, Niklas WeberGraph Neural NetworksNeural-Network Approximation

  25. Operator Neural Jump ODEs: L2L^2-optimal prediction in function spaces

    Jul 25, 2026Florian Krach, Oliver Löthgren, Josef TeichmannNeural Ordinary Differential EquationsNeural-Network Approximation

  26. From Score Approximation to Distribution Approximation in Score-Based Diffusion Models

    Jul 24, 2026Lan V. TruongScore-Based Diffusion ModelNeural-Network Approximation

  27. Boundary-Adapted PINNs for Elliptic Dirichlet Problems: H2(Ω)H^2(Ω) A Priori Error Bounds with Application to Mean Escape Time Computation

    Jul 21, 2026Nathanael Tepakbong, Jun Fan, Xiang Zhou +1Boundary Value ProblemsConventional Physics-Informed Neural Networks

  28. Functional Equivalence and Geometric Diversity in Neural Network Approximations: An Empirical Characterization

    Jul 21, 2026Anuragine S A, Prem JagadeesanNeural-Network ApproximationApproximation

  29. Non-Asymptotic Variational Learning for Monotone Nonlinear Multiscale Elliptic Equations: Scale-Robust Primal-Dual Bounds and Strong-Form Statistical Ill-Conditioning

    Jul 17, 2026Ronald KatendeVariationalMultiscale Dynamics

  30. NeuralChaos: Optimal Adapted Approximation of Square Integrable Predictable Processes

    Jul 15, 2026Anastasis Kratsios, Giulia Livieri, Philipp SchmockerNeural-Network ApproximationStochastic Systems

  31. Approximation of solutions of parameter-dependent problems by residual neural networks

    Jul 15, 2026Ana CarpioNeural-Network ApproximationNeural Network

  32. Deep Learning-based Surrogate Modelling of the LOD Method for Multiscale Problems

    Jul 14, 2026Marc Haltmayer, Jaemin Seo, Yuseung Lee +3Multiscale DynamicsBoundary Value Problems

  33. Approximation of Analytic Functions by ReLU Neural Networks with Adjustable Depth and Width

    Jul 12, 2026Yanming Lai, Defeng Sun, Yang WangRectified Linear Unit NetworksNeural-Network Approximation

  34. An optimal control approach for neural network architecture adaptation with a posteriori error estimation

    Jul 8, 2026C G Krishnanunni, Thomas Scott, Tan Bui-ThanhNeural-Network ApproximationNeural Network Optimization

  35. On Explicit Super-Expressive Approximation for Neural Networks

    Jul 7, 2026Feng-Lei Fan, Ze-Yu Li, Chen-Yu Wang +1Neural-Network ApproximationApproximation

  36. A Convex Approximation Framework for Neural Likelihood-Based Bayesian Inverse Problems

    Jul 7, 2026Fabian Schneider, Tapio Helin, Leila TaghizadehIll-Posed Inverse ProblemNeural-Network Approximation

  37. Minimum Block Width for Universal Approximation by Residual Neural Networks with Inner Width One

    Jul 6, 2026Qi Zhou, Xuan Zhou, Xiao-Song YangNeural-Network ApproximationResidual Connections

  38. From Spectral Methods to Sample Complexity Bounds for Fourier Neural Operators

    Jul 1, 2026Nisha Chandramoorthy, Daniel Sanz-Alonso, Nathan WaniorekFourier Neural OperatorsNeural Operators

  39. Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains

    Jun 30, 2026Haixin Wang, Haoning Dang, Fei Wang +1Partial Differential EquationsBayesian Quadrature

  40. A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch

    Jun 28, 2026Xichuan ZhangStochastic Differential EquationsNeural-Network Approximation

  41. Algorithmic Foundations of Deep Learning: Complexity-Theoretic Rates and a Characterization of Universal Approximation

    Jun 25, 2026Anastasis Kratsios, Simone Brugiapaglia, Bum Jun Kim +2Neural-Network ApproximationApproximation

  42. EML Trees Are Universal Approximators

    Jun 22, 2026Joe Germany, Elie Abdo, Joseph BakarjiNeural-Network ApproximationApproximation

  43. Recurrent neural networks approximate continuous functions

    Jun 18, 2026Valentin Abadie, Clemens Hutter, Helmut BölcskeiNeural-Network ApproximationRecurrent Neural Networks

  44. Generalization Guarantees for Multi-Input Neural Operator Learning in Sobolev Spaces

    Jun 16, 2026Yahong Yang, Zecheng Zhang, Wei Zhu +2Logarithmic Sobolev InequalitiesProbabilistic Operator Learning

  45. Finsler Geometry, Graph Neural Networks, and You

    Jun 15, 2026T. Mitchell Roddenberry, Richard G. BaraniukGraph LaplaciansGraph Neural Networks

  46. Sobolev Approximation by Fixed-Size Neural Networks with Arbitrary Accuracy

    Jun 15, 2026Baicheng Li, Haizhao Yang, Shijun ZhangNeural-Network ApproximationLogarithmic Sobolev Inequalities

  47. The Information-Theoretic Benefit of Shared Representations under Orthogonality Constraints

    Jun 14, 2026Thomas Dittrich, Oliver Potocki, Philipp GrohsNeural-Network ApproximationInformation-Theoretic Limits

  48. SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operators

    Jun 9, 2026Pengqing Shi, Jie Yin, Stephen Tierney +1Fourier Neural OperatorsNeural Operators

  49. Convergence Rates for Neural-Network Estimation with Current-Status Data

    Jun 8, 2026Yuan Wu, Tianhui ZhouTime-To-Event DataNeural-Network Approximation

  50. Weighted universal approximation of differentiable maps on infinite-dimensional manifolds

    Jun 8, 2026Philipp Schmocker, Josef TeichmannNeural-Network ApproximationApproximation

  51. Fourier Neural Operators with rank-1 lattice points and hyperbolic cross

    Jun 7, 2026Jakob Dilen, Alexander Keller, Frances Y. Kuo +1Fourier Neural OperatorsFourier

  52. Where the Score Lives: A Wavelet View of Diffusion

    Jun 6, 2026Emma Finn, Binxu Wang, T. Anderson Keller +1Score-Based Diffusion ModelDiscrete Diffusion Model

  53. Shortcomings and capacities of real-constrained neural networks in complex spaces

    Jun 3, 2026Andrew GracykNeural-Network ApproximationNeural Network

  54. Hierarchical RBF-KAN and RBF-SKAN Architectures for Multidimensional Function Approximation and Random Field Learning

    Jun 1, 2026Mingtao Xia, Qijing ShenRadial Basis FunctionKolmogorov-Arnold Networks

  55. Neural Network Compression by Approximate Differential Equivalence

    May 31, 2026Ravi Dhiman, Andrea Passarella, Mirco Tribastone +1Neural-Network ApproximationNeural Network

  56. Variation Spaces for Encoder--Decoder Neural Operators: Approximation and Generalization

    May 31, 2026Jia-Qi Yang, Lei ShiNeural OperatorsNeural-Network Approximation

  57. Approximation and learning of anisotropic and mixed smooth functions by deep ReLU neural networks

    May 29, 2026Yunfei Yang, Jun FanLogarithmic Sobolev InequalitiesNeural-Network Approximation

  58. Pretrained Approximators for Low-Thrust Trajectory Cost and Reachability

    May 26, 2026Zhong Zhang, Giacomo Acciarini, Dario Izzo +2Trajectory OptimizationNeural-Network Approximation

  59. Random Neural Network Expressivity for Non-Linear Partial Differential Equations

    May 24, 2026Muhammed Ali Mehmood, Lukas GononPartial Differential EquationsNeural-Network Approximation

  60. IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients

    May 24, 2026Shan Zhong, George BirosFourier Neural OperatorsPartial Differential Equations