Neural Networks Optimally Compress the Sawbridge

2021 Data Compression Conference (DCC)(2021)

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摘要
Neural-network-based compressors have proven to be remarkably effective at compressing sources, such as images, that are nominally high-dimensional but presumed to be concentrated on a low-dimensional manifold. We consider a continuous-time random process that models an extreme version of such a source, wherein the realizations fall along a one-dimensional “curve” in function space that has infini...
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关键词
Manifolds,Image coding,Neural networks,Stochastic processes,Data compression,Compressors,Karhunen-Loeve transforms
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