Deep neural networks have an inbuilt Occam’s razor
The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions exp...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Nature Research
2025
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