ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2007.06007
  4. Cited By
Universal Approximation Power of Deep Residual Neural Networks via
  Nonlinear Control Theory

Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory

12 July 2020
Paulo Tabuada
Bahman Gharesifard
ArXivPDFHTML

Papers citing "Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory"

3 / 3 papers shown
Title
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of
  Experts
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts
Anastasis Kratsios
Haitz Sáez de Ocáriz Borde
Takashi Furuya
Marc T. Law
MoE
41
1
0
05 Feb 2024
Learning on Manifolds: Universal Approximations Properties using
  Geometric Controllability Conditions for Neural ODEs
Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
Karthik Elamvazhuthi
Xuechen Zhang
Samet Oymak
Fabio Pasqualetti
AI4CE
19
6
0
15 May 2023
Universal Approximation Property of Hamiltonian Deep Neural Networks
Universal Approximation Property of Hamiltonian Deep Neural Networks
M. Zakwan
M. d’Angelo
Giancarlo Ferrari-Trecate
28
5
0
21 Mar 2023
1