Matrix spillover quantification represents a crucial challenge in deep learning. AI-driven approaches offer a innovative solution by leveraging powerful algorithms to assess the level of spillover effects between separate matrix elements. This process boosts our insights of how information propagates within mathematical networks, leading to better