Similarity scores released for How do Variational Autoencoders Learn? Insights from Representational Similarity
Bonheme, L. and Grzes, M. (2022) Similarity scores released for How do Variational Autoencoders Learn? Insights from Representational Similarity. [Data Collection]
Description
This repository contains more than 45 million of similarity scores used in "How do Variational Autoencoders Learn? Insights from Representational Similarity".
| Uncontrolled keywords: | VAE; representational similarity; representation learning; deep learning; variational autoencoders | ||
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| Subjects: | Q Science > Q Science (General) > Q335 Artificial intelligence Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.87 Neural computers, neural networks |
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| DOI: | 10.22024/UniKent/01.01.444 | ||
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing | ||
| Depositing User: | Lisa Bonheme | ||
| Collection period: | From To 1 December 2021 20 May 2022 |
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| Last Modified: | 06 Jul 2022 14:14 | ||
| Publication Date: | 6 July 2022 | ||
| URI: | https://data.kent.ac.uk/id/eprint/444 | ||
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https://orcid.org/0000-0002-9166-3971
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