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Linearization of Neural Networks as a Dual Framework for Stability and Sparsity

Zheng, Caleb2026

… extension inspired by finite-time Lyapunov exponents that resolves this incompatibility and recovers generation quality after pruning. Together, these contributions establish linearization as a versatile theoretical language for both analysis and deployment of neural networks.

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