Verification-friendly Networks: the Case for Parametric ReLUs
Author:
Affiliation:
1. Imperial College London,Department of Computing,London,United Kingdom
Funder
Royal Academy of Engineering
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191169.pdf?arnumber=10191169
Reference50 articles.
1. Bias field robustness verification of large neural image classifiers;henriksen;Proceedings of the 32nd British Machine Vision Conference (BMVC21),0
2. DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis
3. Towards Scalable Complete Verification of Relu Neural Networks via Dependency-based Branching
4. The Marabou Framework for Verification and Analysis of Deep Neural Networks
5. Efficient neural network verification via adaptive refinement and adversarial search;henriksen;Proceedings of the 24th European Conference on Artificial Intelligence (ECAI20),0
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