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Approximation of Neural Networks for Verification
Publikationstyp
Conference Paper
Date Issued
2019-04
Sprache
English
Author(s)
Institut
TORE-URI
Start Page
17
End Page
26
Citation
Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV 2019)
Scopus ID
Statistical learning methods enable the adaptation of artificial neural networks (ANN) to complex problems. Meanwhile, formal properties can be verified on small ANNs under simplified assumptions. First we show a simple algorithm to convert neural networks into a system of equations with boundary conditions. In particular, we discuss how non-linear functions may be approximated. In experiments we study the impact of this approximation on the validity on the proof of formal guarantees.