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Training Provably Robust Models by Polyhedral Envelope Regularization

Training Provably Robust Models by Polyhedral Envelope Regularization

10 December 2019
Chen Liu
Mathieu Salzmann
Sabine Süsstrunk
    AAML
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Papers citing "Training Provably Robust Models by Polyhedral Envelope Regularization"

2 / 2 papers shown
Title
The Fundamental Limits of Interval Arithmetic for Neural Networks
The Fundamental Limits of Interval Arithmetic for Neural Networks
M. Mirman
Maximilian Baader
Martin Vechev
32
6
0
09 Dec 2021
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
234
1,837
0
03 Feb 2017
1