Cover Image

Universal approximation property of ODENet and ResNet with a single activation function

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kimura, Masato, Matsui, Kazunori, Mizuno, Yosuke
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Numerical Analysis 37M15, 41A46, 41A63, 65L12, 68T07, 65P99
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SUPN: Shallow Universal Polynomial Networks
by: Morrow, Zachary, et al.
Published: (2025)

Sparse and low-rank approximations of parametric elliptic PDEs: the best of both worlds
by: Bachmayr, Markus, et al.
Published: (2025)

Enhancing Future Prediction of Linear and Nonlinear Reduced-Order Models for Transport-Dominated Problems Using Lagrangian Data
by: Li, Meng, et al.
Published: (2026)

Weighted approximate sampling recovery and integration based on B-spline interpolation and quasi-interpolation
by: Dũng, Dinh
Published: (2025)

Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations
by: Chen, Shuang, et al.
Published: (2026)

Weights initialization of neural networks for function approximation
by: Hu, Xinwen, et al.
Published: (2025)

Achieving Universal Approximation and Universal Interpolation via Nonlinearity of Control Families
by: Cai, Yongqiang, et al.
Published: (2025)

On best approximation by multivariate ridge functions with applications to generalized translation networks
by: Geuchen, Paul, et al.
Published: (2024)

An iterative method for the solution of Laplace-like equations in high and very high space dimensions
by: Yserentant, Harry
Published: (2024)

Time-Frequency Analysis for Neural Networks
by: Abdeljawad, Ahmed, et al.
Published: (2025)

Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation
by: Li, Li'ang, et al.
Published: (2023)

A Low Rank Neural Representation of Entropy Solutions
by: Rim, Donsub, et al.
Published: (2024)

A theoretical analysis on the inversion of matrices via Neural Networks designed with Strassen algorithm
by: Romera, Gonzalo, et al.
Published: (2025)

Approximation and Gradient Descent Training with Neural Networks
by: Welper, G.
Published: (2024)

Vanilla Feedforward Neural Networks as a Discretization of Dynamical Systems
by: Duan, Yifei, et al.
Published: (2022)

Optimal approximation of infinite-dimensional holomorphic functions II: recovery from i.i.d. pointwise samples
by: Adcock, Ben, et al.
Published: (2023)

A Minimal Control Family of Dynamical Systems for Universal Approximation
by: Duan, Yifei, et al.
Published: (2023)

Christoffel Adaptive Sampling for Sparse Random Feature Expansions
by: Adcock, Ben, et al.
Published: (2026)

Quasi-interpolation for high-dimensional function approximation
by: Gao, Wenwu, et al.
Published: (2024)

Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel
by: Khamlich, Moaad, et al.
Published: (2023)

Weighted least $\ell_p$ approximation on compact Riemannian manifolds
by: Li, Jiansong, et al.
Published: (2024)

A lattice algorithm with multiple shifts for function approximation in Korobov spaces
by: Cai, Mou, et al.
Published: (2025)

Neural empirical interpolation method for nonlinear model reduction
by: Hirsch, Max, et al.
Published: (2024)

Comparative study on higher order compact RBF-FD formulas with Gaussian and Multiquadric radial functions
by: Yadav, Manoj Kumar, et al.
Published: (2024)

Hyperbolic trigonometric functions as approximation kernels and their properties II: Wavelets
by: Buhmann, M., et al.
Published: (2025)

A universal approximation theorem and its applications to vector lattice theory
by: Bilokopytov, Eugene, et al.
Published: (2025)

A study on $\mr{F}$-simultaneous approximative $τ$-compactness property in Banach spaces
by: Das, Syamantak, et al.
Published: (2025)

Entropy-based convergence rates of greedy algorithms
by: Li, Yuwen, et al.
Published: (2023)

Streaming Compression of Scientific Data via weak-SINDy
by: Russo, Benjamin P., et al.
Published: (2023)

Algorithms for pointwise and piecewise polynomial approximations to the trigonometric functions
by: Phuong, Quan Le
Published: (2025)

A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks
by: Chen, Shi, et al.
Published: (2021)

Random Projection Neural Networks of Best Approximation: Convergence theory and practical applications
by: Fabiani, Gianluca
Published: (2024)

Function values are enough for $L_2$-approximation: Part II
by: Krieg, David, et al.
Published: (2020)

Error bounds for numerical differentiation using kernels of finite smoothness
by: Davydov, Oleg
Published: (2025)

New universal operator approximation theorem for encoder-decoder architectures (Preprint)
by: Gödeke, Janek, et al.
Published: (2025)

A new analysis of empirical interpolation methods and Chebyshev greedy algorithms
by: Li, Yuwen
Published: (2024)

A General Weighting Theory for Ensemble Learning: Beyond Variance Reduction via Spectral and Geometric Structure
by: Fokoué, Ernest
Published: (2025)

PODNO: Proper Orthogonal Decomposition Neural Operators
by: Cheng, Zilan, et al.
Published: (2025)

A Universal Approximation Theorem for Neural Networks with Outputs in Locally Convex Spaces
by: Saini, Sachin
Published: (2026)

On finite-dimensional encoding/decoding theorems for neural operators
by: Oliveira, Vinícius Luz, et al.
Published: (2026)