Interpreting CNN Models for Apparent Personality Trait Regression

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Unsupervised Learning of Neural Networks to Explain Neural Networks (2018, background): “Other studies retrieved mid-level representations with specific meanings from CNNs for various applications [15, 35, 32, 19].”
Interpretable Convolutional Neural Networks (2017, background): “[11, 31, 29, 15] selected neural units with specific meanings from CNNs for various applications.”
Understanding the Political Ideology of Legislators from Social Media Images (2019, methodology): “r election prediction) Several methods have been proposed to automatically infer perceived (apparent) personality from visual cues (Escalante et al., 2018, Escalera et al., 2018, Junior et al., 2018, Ventura, Masip, and Lapedriza, 2017), and a recent study demonstrated that a similar automated metho”
Visualizing Apparent Personality Analysis with Deep Residual Networks (2017, background): “Previous work found in the literature proposed to explore the relationship between image features and first impressions [20, 18] in order to determine which region is more relevant to predict different personality traits.”
Recent trends in deep learning based personality detection (2019, methodology): “2 Class activation map used by [99] for interpreting CNN models.”