The reusability prior: comparing deep learning models without training
Various choices can affect the performance of deep learning models. We conjecture that differences in the number of contexts for model components during training are critical. We generalize this notion by defining the reusability prior as follows: model components are forced to function in diverse c...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2023-01-01
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| Series: | Machine Learning: Science and Technology |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-2153/acc713 |