Learning to compute inner consensus: A novel approach to modeling agreement between Capsules

Gonçalo Faria

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arXiv · 1909.12737

Learning to compute inner consensus: A novel approach to modeling agreement between Capsules

Gonçalo Faria

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Abstract

This project considers Capsule Networks, a recently introduced machine learning model that has shown promising results regarding generalization and preservation of spatial information with few parameters. The Capsule Network's inner routing procedures thus far proposed, a priori, establish how the routing relations are modeled, which limits the expressiveness of the underlying model. In this project, we propose two distinct ways in which the routing procedure can be learned like any other network parameter.

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Gonçalo Faria. 2019-09-27. Learning to compute inner consensus: A novel approach to modeling agreement between Capsules. https://arxiv.org/abs/1909.12737

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