Fully connected ReLU networks attain minimax-optimal nonparametric regression rates under temporal-spatial dependence with functional spatial noise, up to logarithmic factors.
On total variation minimization and surface evolution using parametric maximum flows
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Dense ReLU Neural Networks for Temporal-spatial Model
Fully connected ReLU networks attain minimax-optimal nonparametric regression rates under temporal-spatial dependence with functional spatial noise, up to logarithmic factors.