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Marco Ancona

2 accepted papers

2019

Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation

ICML 2019oral

The problem of explaining the behavior of deep neural networks has recently gained a lot of attention. While several attribution methods have been proposed, most come without strong theoretical foundations, which raises questions about their reliability. On the other hand, the literature on cooperat…

Cited by 319SourcePDFScholar
2018

Towards better understanding of gradient-based attribution methods for Deep Neural Networks

ICLR 2018poster

Understanding the flow of information in Deep Neural Networks (DNNs) is a challenging problem that has gain increasing attention over the last few years. While several methods have been proposed to explain network predictions, there have been only a few attempts to compare them from a theoretical pe…