Unveiling Feature Dynamics: Weight Space Correlation Analysis in Deep Learning

The research on Weight Space Correlation Analysis offers a novel method to understand how features are utilized within deep learning models, potentially leading to more efficient and interpretable model designs. Analyzing weight space correlations could improve model explainability and facilitate the identification of redundant or critical features.

• •Focuses on understanding feature utilization within deep learning models.
• •Utilizes weight space correlation analysis as a core methodology.
• •Aims to improve model explainability and identify key features.