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cs.LG2026
Faster Verified Explanations for Neural Networks
Alessandro De Palma, Greta Dolcetti, Caterina Urban
Verified explanations are a principled way to explain the decisions taken by neural networks, which are otherwise black-box in nature. However, these techniques face significant sc…
cs.LG2024
Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation
Ben Batten, Yang Zheng, Alessandro De Palma +2
We address the problem of verifying neural networks against geometric transformations of the input image, including rotation, scaling, shearing, and translation. The proposed metho…