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Selvaraju, R.R., Das, A., Vedantam, R., Cogswell, M., Parikh, D. and Batra, D. (2016) Grad-Cam: Why Did You Say That? Visual Explanations from Deep Networks via Gradient-Based Localization. 2017 IEEE International Conference on Computer Vision, Venice, Italy, 22-29 October 2017, 618-626.
https://doi.org/10.1109/ICCV.2017.74

has been cited by the following article:

• TITLE: New Trend in Fintech: Research on Artificial Intelligence Model Interpretability in Financial Fields

  AUTHORS: Han Yan, Sheng Lin

  KEYWORDS: Fintech, Regtech, AI, Model Interpretability, LIMER

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.9 No.10, October 24, 2019

  ABSTRACT: With the development of Fintech, applying artificial intelligence (AI) technologies to the financial field is a general trend. However, there are some inappropriate conditions, for instance, the AI model is always treated as a black box and cannot be interpreted. This paper studies the AI model interpretability when the models are applied in the financial field. We analyze the reasons of black box problem and explore the effective solutions. We propose a new kind of automatic Regtech tool—LIMER, and put forward policy suggestions, thereby continuously promoting the development of Fintech to a higher level.