Gaussian Prototypical Networks for Few-Shot Learning on Omniglot

@article{Fort2018GaussianPN,
  title={Gaussian Prototypical Networks for Few-Shot Learning on Omniglot},
  author={Stanislav Fort},
  journal={ArXiv},
  year={2018},
  volume={abs/1708.02735}
}
We propose a novel architecture for k-shot classification on the Omniglot dataset. Building on prototypical networks, we extend their architecture to what we call Gaussian prototypical networks. Prototypical networks learn a map between images and embedding vectors, and use their clustering for classification. In our model, a part of the encoder output is interpreted as a confidence region estimate about the embedding point, and expressed as a Gaussian covariance matrix. Our network then… CONTINUE READING
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