Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds

Empirical results, however,suggest thatnetworks of moderate size already yield appealing performance. To explain such a gap, a common belief is that many data sets exhibit low dimensional structures, and can be modeled as samples near a low dimensional manifold.