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most citedActive operator inference for learning low-dimensional dynamical-system models from noisy data

2 citations · 5 across the 13 of their papers we have counts for

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stat.ML2024

How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning

Arthur Jacot, Seok Hoan Choi, Yuxiao Wen

We show that deep neural networks (DNNs) can efficiently learn any composition of functions with bounded -norm, which allows DNNs to break the curse of dimensionality in way…