Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions

• URL: http://arxiv.org/abs/2311.10780v1
• Date: Thu, 16 Nov 2023 11:01:39 GMT
• Title: Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions
• Authors: L\'aszl\'o Antal (RWTH Aachen University), Hana Masara (RWTH Aachen University), Erika \'Abrah\'am (RWTH Aachen University)
• Abstract summary: We extend an available neural network verification technique to support a wider class of piece-wise linear activation functions. We also extend the algorithms, which provide in their original form exact respectively over-approximative results for bounded input sets represented as start sets, to allow also unbounded input set.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we extend an available neural network verification technique to support a wider class of piece-wise linear activation functions. Furthermore, we extend the algorithms, which provide in their original form exact respectively over-approximative results for bounded input sets represented as start sets, to allow also unbounded input set. We implemented our algorithms and demonstrated their effectiveness in some case studies.

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