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Representational Distance Learning for Deep Neural Networks
Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Represen...
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| Udgivet i: | Front Comput Neurosci |
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| Main Authors: | , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Frontiers Media S.A.
2016
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5187453/ https://ncbi.nlm.nih.gov/pubmed/28082889 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2016.00131 |
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