Memory-Efficient Implementation of DenseNets

21 Jul 2017Geoff PleissDanlu ChenGao HuangTongcheng LiLaurens van der MaatenKilian Q. Weinberger

The DenseNet architecture is highly computationally efficient as a result of feature reuse. However, a naive DenseNet implementation can require a significant amount of GPU memory: If not properly managed, pre-activation batch normalization and contiguous convolution operations can produce feature maps that grow quadratically with network depth... (read more)

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