10 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 4 cited
An Extension of LIME with Improvement of Interpretability and Fidelity
Sheng Shi, Yangzhou Du, Wei Fan
While deep learning makes significant achievements in Artificial Intelligence (AI), the lack of transparency has limited its broad application in various vertical domains. Explaina…
cs.LG2020★ 8 cited
A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation
Sheng Shi, Xinfeng Zhang, Wei Fan
Explainability is a gateway between Artificial Intelligence and society as the current popular deep learning models are generally weak in explaining the reasoning process and predi…
cs.LG2019★ 10 cited
Explaining the Predictions of Any Image Classifier via Decision Trees
Sheng Shi, Xinfeng Zhang, Wei Fan
Despite outstanding contribution to the significant progress of Artificial Intelligence (AI), deep learning models remain mostly black boxes, which are extremely weak in explainabi…