90 citations · 90 across the 1 of their papers we have counts for
2 papers
cs.AI2021★ 90 cited
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations
Sérgio Jesus, Catarina Belém, Vladimir Balayan +4
There have been several research works proposing new Explainable AI (XAI) methods designed to generate model explanations having specific properties, or desiderata, such as fidelit…
cs.LG2020
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations
João Bento, Pedro Saleiro, André F. Cruz +2
Although recurrent neural networks (RNNs) are state-of-the-art in numerous sequential decision-making tasks, there has been little research on explaining their predictions. In this…