Restyling Unsupervised Concept Based Interpretable Networks with
Generative Models
Restyling Unsupervised Concept Based Interpretable Networks with
Generative Models
Developing inherently interpretable models for prediction has gained prominence in recent years. A subclass of these models, wherein the interpretable network relies on learning high-level concepts, are valued because of closeness of concept representations to human communication. However, the visualization and understanding of the learnt unsupervised dictionary of concepts encounters …