Matrix spillover quantification measures a crucial challenge in deep learning. AI-driven approaches offer a promising solution by leveraging powerful algorithms to analyze the magnitude of spillover effects between different matrix elements. This process boosts our insights of how information flows within mathematical networks, leading to more mode