Neural arithmetic logic units
Neural networks can learn to represent and manipulate numerical information, but they seldom generalize well outside of the range of numerical values encountered during training. To encourage more systematic numerical extrapolation, we propose an architecture that represents numerical quantities as...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Curran Associates
2019
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