Subhomogeneous Deep Equilibrium Models
International Conference on Machine Learning (ICML), 2024
Implicit-depth neural networks have grown as powerful alternatives to traditional networks in various applications in recent years. However, these models often lack guarantees of existence and uniqueness, raising stability, performance, and reproducibility issues. In this paper, we present a new analysis of the …