Streamlining latent spaces in machine learning using moment pooling
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DOI: 10.1103/physrevd.110.074020
Abstract: Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose “moment pooling,” a natural extension of deep sets networks which… read more here.
Keywords: streamlining latent; machine learning; moment; moment pooling ... See more keywords