Deep Equilibrium Models Now Proven to Work with Any Activation Function, Converge Predictably

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Overview

• Research proves global convergence of Deep Equilibrium Models with general activation functions
• Shows linear convergence rate to optimal solutions with quadratic loss
• Introduces novel population Gram matrix approach
• Develops new dual activation using Hermite polynomials
• Expands beyond ReLU to any activation with bounded derivatives

Plain English Explanation

Deep Equilibrium Models are like a recipe that keeps getting refined until it's just right. Traditional neural networks stack many layers, but DEQs find a sweet spot where adding more layers doesn't change the outcome.

[Deep Equilibrium Models](https://aimodels.fyi/papers/arxi...

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