Learning Structured Generative Concepts
Many real world concepts, such as “car”, “house”, and “tree”, are more than simply a collection of features. These objects are richly structured, defined in terms of systems of relations, subparts, and recursive embeddings. We describe an approach to concept representation and learning that att...
| Main Authors: | , , |
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| Format: | Article |
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Cognitive Science Society
2017
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| Online Access: | http://hdl.handle.net/1721.1/112758 https://orcid.org/0000-0002-1925-2035 |