Luca Galimberti

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20242026

most citedLow-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach

2 citations · 2 across the 4 of their papers we have counts for

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cs.LG2026

Constructive Universal Approximation by Infinite-Dimensional Neural Networks via Gaussian-Weighted Ridgelet Transform

Sho Sonoda, Luca Galimberti, Yuanchao Xu +2

Neural networks whose inputs are functions, as in operator learning, are usually shown to be universal by existence arguments, either by reduction to finite-dimensional networks or…

math.FA2026

$L^{p}$ approximation results for infinite dimensional Neural Networks

Luca Galimberti

Leveraging the neural architectures which we introduced in arXiv:2109.13512v4, we show a global universal approximation theorem in the topology of $L^{p} (μ)$ , where $1 \leq p < \infty$ a…

Constructive Universal Approximation by Infinite-Dimensional Neural Networks via Gaussian-Weighted Ridgelet Transform

Lp approximation results for infinite dimensional Neural Networks

$L^{p}$ approximation results for infinite dimensional Neural Networks