Improving neural ordinary differential equations via knowledge distillation
Abstract Neural ordinary differential equations (ODEs) (Neural ODEs) construct the continuous dynamics of hidden units using ODEs specified by a neural network, demonstrating promising results on many tasks. However, Neural ODEs still do not perform well on image recognition tasks. The possible reas...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-03-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cvi2.12248 |