Reachability analysis for neural feedback systems using regressive polynomial rule inference-Reference-Cited by-同舟云学术

Reachability analysis for neural feedback systems using regressive polynomial rule inference

Published:2019-04-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and Control
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Author:

Dutta Souradeep¹,Chen Xin²,Sankaranarayanan Sriram¹

Affiliation:

1. University of Colorado

2. University of Dayton

Funder

US NSF

Air Force Research Laboratory

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3302504.3311807

Reference47 articles.

1. HyLAA

2. Osbert Bastani Yani Ioannou Leonidas Lampropoulos Dimitrios Vytiniotis Aditya Nori and Antonio Criminisi. 2016. Measuring neural net robustness with constraints. In Advances in Neural Information Processing Systems. 2613--2621. Osbert Bastani Yani Ioannou Leonidas Lampropoulos Dimitrios Vytiniotis Aditya Nori and Antonio Criminisi. 2016. Measuring neural net robustness with constraints. In Advances in Neural Information Processing Systems. 2613--2621.

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