AI RESEARCH
Understanding the Theoretical Foundations of Deep Neural Networks through Differential Equations
arXiv CS.AI
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ArXi:2603.18331v1 Announce Type: new Deep neural networks (DNNs) have achieved remarkable empirical success, yet the absence of a principled theoretical foundation continues to hinder their systematic development. In this survey, we present differential equations as a theoretical foundation for understanding, analyzing, and improving DNNs.