Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional Semantics

ACL 2020 Guy Emerson

Functional Distributional Semantics provides a linguistically interpretable framework for distributional semantics, by representing the meaning of a word as a function (a binary classifier), instead of a vector. However, the large number of latent variables means that inference is computationally expensive, and training a model is therefore slow to converge... (read more)

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