2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Shifting-based Optimizable Linear Relaxations for General Activation Functions
Philipp Kern, László Antal, Erika Ábráham +1
The use of neural networks (NNs) is rapidly increasing, including in safety- and security-critical domains. To provide formal guarantees about NN behavior, many verification method…
Revisiting Differential Verification: Equivalence Verification with Confidence
Samuel Teuber, Philipp Kern, Marvin Janzen +1
When validated neural networks (NNs) are pruned (and retrained) before deployment, it is desirable to prove that the new NN behaves equivalently to the (original) reference NN. To…
Optimized Symbolic Interval Propagation for Neural Network Verification
Philipp Kern, Marko Kleine Büning, Carsten Sinz
Neural networks are increasingly applied in safety critical domains, their verification thus is gaining importance. A large class of recent algorithms for proving input-output rela…
Geometric Path Enumeration for Equivalence Verification of Neural Networks
Samuel Teuber, Marko Kleine Büning, Philipp Kern +1
As neural networks (NNs) are increasingly introduced into safety-critical domains, there is a growing need to formally verify NNs before deployment. In this work we focus on the fo…