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Approximation Bounds for Random Neural Networks and Reservoir Systems

Approximation Bounds for Random Neural Networks and Reservoir Systems

14 February 2020
Lukas Gonon
Lyudmila Grigoryeva
Juan-Pablo Ortega
ArXivPDFHTML

Papers citing "Approximation Bounds for Random Neural Networks and Reservoir Systems"

12 / 12 papers shown
Title
Online Federation For Mixtures of Proprietary Agents with Black-Box Encoders
Online Federation For Mixtures of Proprietary Agents with Black-Box Encoders
Xuwei Yang
Fatemeh Tavakoli
D. B. Emerson
Anastasis Kratsios
FedML
62
0
0
30 Apr 2025
How more data can hurt: Instability and regularization in next-generation reservoir computing
How more data can hurt: Instability and regularization in next-generation reservoir computing
Yuanzhao Zhang
Edmilson Roque dos Santos
Sean P. Cornelius
77
2
0
28 Jan 2025
Deep Kalman Filters Can Filter
Deep Kalman Filters Can Filter
Blanka Hovart
Anastasis Kratsios
Yannick Limmer
Xuwei Yang
45
1
0
31 Dec 2024
Expressivity of Neural Networks with Random Weights and Learned Biases
Expressivity of Neural Networks with Random Weights and Learned Biases
Ezekiel Williams
Avery Hee-Woon Ryoo
Thomas Jiralerspong
Alexandre Payeur
M. Perich
Luca Mazzucato
Guillaume Lajoie
31
2
0
01 Jul 2024
Universal randomised signatures for generative time series modelling
Universal randomised signatures for generative time series modelling
Francesca Biagini
Lukas Gonon
Niklas Walter
40
4
0
14 Jun 2024
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs
Ariel Neufeld
Philipp Schmocker
Sizhou Wu
37
7
0
08 May 2024
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
Unsupervised Random Quantum Networks for PDEs
Unsupervised Random Quantum Networks for PDEs
Josh Dees
Antoine Jacquier
Sylvain Laizet
16
2
0
21 Dec 2023
Error Bounds for Learning with Vector-Valued Random Features
Error Bounds for Learning with Vector-Valued Random Features
S. Lanthaler
Nicholas H. Nelsen
27
12
0
26 May 2023
Chaotic Hedging with Iterated Integrals and Neural Networks
Chaotic Hedging with Iterated Integrals and Neural Networks
Ariel Neufeld
Philipp Schmocker
31
10
0
21 Sep 2022
Echo State Networks trained by Tikhonov least squares are L2(μ)
  approximators of ergodic dynamical systems
Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems
Allen G. Hart
J. Hook
Jonathan H.P Dawes
11
46
0
14 May 2020
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions
  with $ \ell^1 $ and $ \ell^0 $ Controls
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with ℓ1 \ell^1 ℓ1 and ℓ0 \ell^0 ℓ0 Controls
Jason M. Klusowski
Andrew R. Barron
127
142
0
26 Jul 2016
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