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cs.LG2023
Causal Analysis for Robust Interpretability of Neural Networks
Ola Ahmad, Nicolas Bereux, Loïc Baret +2
Interpreting the inner function of neural networks is crucial for the trustworthy development and deployment of these black-box models. Prior interpretability methods focus on corr…
cs.LG2022★ 1 cited
Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks
Vahid Hashemi, Jan Křetínsky, Sabine Rieder +1
Runtime monitoring provides a more realistic and applicable alternative to verification in the setting of real neural networks used in industry. It is particularly useful for detec…