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pro vyhledávání: '"Yolcu, Galip Ümit"'
Local data attribution (or influence estimation) techniques aim at estimating the impact that individual data points seen during training have on particular predictions of an already trained Machine Learning model during test time. Previous methods e
Externí odkaz:
http://arxiv.org/abs/2402.12118
Autor:
Pahde, Frederik, Yolcu, Galip Ümit, Binder, Alexander, Samek, Wojciech, Lapuschkin, Sebastian
Explainable AI (XAI) is slowly becoming a key component for many AI applications. Rule-based and modified backpropagation XAI approaches however often face challenges when being applied to modern model architectures including innovative layer buildin
Externí odkaz:
http://arxiv.org/abs/2211.17174