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20182025
most citedUniversal Approximation Property of Neural Ordinary Differential Equations

20 citations · 60 across the 24 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

math.FA2022★ 1 cited

Global universality of the two-layer neural network with the -rectified linear unit

N. Hatano, M. Ikeda, I. Ishikawa +1

This paper concerns the universality of the two-layer neural network with the -rectified linear unit activation function with with a suitable norm without any res…

cs.DM2022

Dynamic Structure Estimation from Bandit Feedback using Nonvanishing Exponential Sums

Motoya Ohnishi, Isao Ishikawa, Yuko Kuroki +1

This work tackles the dynamic structure estimation problems for periodically behaved discrete dynamical system in the Euclidean space. We assume the observations become sequentiall…

cs.LG2022★ 1 cited

Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups

Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

We show the universality of depth-2 group convolutional neural networks (GCNNs) in a unified and constructive manner based on the ridgelet theory. Despite widespread use in applica…

cs.LG2022★ 9 cited

Universal approximation property of invertible neural networks

Isao Ishikawa, Takeshi Teshima, Koichi Tojo +3

Invertible neural networks (INNs) are neural network architectures with invertibility by design. Thanks to their invertibility and the tractability of Jacobian, INNs have various m…

math.DS2022★ 15 cited

Koopman and Perron-Frobenius Operators on reproducing kernel Banach spaces

Masahiro Ikeda, Isao Ishikawa, Corbinian Schlosser

Koopman and Perron-Frobenius operators for dynamical systems have been getting popular in a number of fields in science these days. Properties of the Koopman operator essentially d…

cs.LG2022★ 3 cited

Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis

Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

Neural network on Riemannian symmetric space such as hyperbolic space and the manifold of symmetric positive definite (SPD) matrices is an emerging subject of research in geometric…