Nov. 11, 2022, 2:11 a.m. | Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan

cs.LG updates on arXiv.org arxiv.org

We present a new convolution layer for deep learning architectures which we
call QuadConv -- an approximation to continuous convolution via quadrature. Our
operator is developed explicitly for use on unstructured data, and accomplishes
this by learning a continuous kernel that can be sampled at arbitrary
locations. In the setting of neural compression, we show that a QuadConv-based
autoencoder, resulting in a Quadrature Convolutional Neural Network (QCNN), can
match the performance of standard discrete convolutions on structured uniform
data, as …

application arxiv compression convolutional neural network data data compression network neural network unstructured data

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