We have located links that may give you full text access.
Functional loops: Monitoring functional organization of deep neural networks using algebraic topology.
Various topological methods have emerged in recent years to investigate the inner workings of deep neural networks (DNNs) based on the structural and weight information. However, their effectiveness is restricted due to the stratified structure and volatile weight information. In this study, we explore the relationship between functional organizations and network performance using algebraic topology. Our results indicate that functional loops reveal functional interaction patterns of multiple neurons in DNNs. We also propose functional persistence as a measure of functional complexity and develop an early stopping criterion that achieves competitive results without requiring a validation set.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app