The softmax function is ubiquitous in machine learning and optimization applications.

It is common to assess a model's merit for scientific discovery, and thus novel insights, by how well it aligns with already available domain

Recently, a series of diffusion-aware distillation algorithms have emerged to alleviate the computational overhead associated with the multi-step inference process of Diffusion Models (DMs).

This makes CDE particularly useful in critical application domains. However, interpretable CDE methods are understudied.