PI: Dejing Dou

The goal of this project is to evaluate contemporary techniques for deep learning model explanations and utilize DL Explanation approach for improving model interpretability.

Methods

• Utilizing feature importance methods
  for dimensionality reduction and
  explanation generation
• Generating representations of the
  latent feature space of a model via
  feature importance
• User survey to evaluate
  interpretability of class specific label
  representations