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Verifying Safety of Neural Networks from Topological Perspectives

Verifying Safety of Neural Networks from Topological Perspectives

27 June 2023
Zhen Liang
Dejin Ren
Bai Xue
J. Wang
Wenjing Yang
Wanwei Liu
    AAML
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Papers citing "Verifying Safety of Neural Networks from Topological Perspectives"

5 / 5 papers shown
Title
Open- and Closed-Loop Neural Network Verification using Polynomial
  Zonotopes
Open- and Closed-Loop Neural Network Verification using Polynomial Zonotopes
Niklas Kochdumper
Christian Schilling
Matthias Althoff
Stanley Bak
19
32
0
06 Jul 2022
On The Verification of Neural ODEs with Stochastic Guarantees
On The Verification of Neural ODEs with Stochastic Guarantees
Sophie Gruenbacher
Ramin Hasani
Mathias Lechner
J. Cyranka
S. Smolka
Radu Grosu
66
31
0
16 Dec 2020
Output Reachable Set Estimation and Verification for Multi-Layer Neural
  Networks
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks
Weiming Xiang
Hoang-Dung Tran
Taylor T. Johnson
72
290
0
09 Aug 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
222
1,835
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
931
0
21 Oct 2016
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