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Universal Approximation of Input-Output Maps by Temporal Convolutional
  Nets

Universal Approximation of Input-Output Maps by Temporal Convolutional Nets

21 June 2019
Joshua Hanson
Maxim Raginsky
    AI4TS
ArXivPDFHTML

Papers citing "Universal Approximation of Input-Output Maps by Temporal Convolutional Nets"

4 / 4 papers shown
Title
Theoretical Foundations of Deep Selective State-Space Models
Theoretical Foundations of Deep Selective State-Space Models
Nicola Muca Cirone
Antonio Orvieto
Benjamin Walker
C. Salvi
Terry Lyons
Mamba
66
26
0
29 Feb 2024
Dimension reduction in recurrent networks by canonicalization
Dimension reduction in recurrent networks by canonicalization
Lyudmila Grigoryeva
Juan-Pablo Ortega
29
19
0
23 Jul 2020
Temporal Information Processing on Noisy Quantum Computers
Temporal Information Processing on Noisy Quantum Computers
Jiayin Chen
H. Nurdin
N. Yamamoto
21
86
0
26 Jan 2020
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhehuai Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
718
6,750
0
26 Sep 2016
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