Fisher-rao metric, geometry, and complexity of neural networks
© 2019 by the author(s). We study the relationship between geometry and capacity measures for deep neural networks from an invariance viewpoint. We introduce a new notion of capacity - the Fisher-Rao norm - that possesses desirable invariance properties and is motivated by Information Geometry. We d...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/138296 |