Refinement and Universal Approximation via Sparsely Connected ReLU Convolution Nets
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DOI: 10.1109/lsp.2020.3005051
Abstract: We construct a highly regular and simple structured class of sparsely connected convolutional neural networks with rectifier activations that provide universal function approximation in a coarse-to-fine manner with increasing number of layers. The networks are… read more here.
Keywords: convolution; sparsely connected; universal approximation; refinement universal ... See more keywords