equivariant-architecture-designer

SKILL.md

This skill helps you design neural network architectures that respect identified symmetry groups. Given a validated group specification, it recommends architecture patterns, specific libraries, and implementation strategies.

The payoff: Equivariant architectures have fewer parameters, train faster, generalize better, and are more robust to distribution shift.

Gather the validated group specification. Confirm: which group(s) are involved, whether invariance or equivariance is needed, the data domain (images, point clouds, graphs, etc.), task type (classification, regression, generation), and any computational constraints. If group isn't specified, work with user to identify it first.

當您已驗證對稱組並需要設計尊重這些對稱性的神經網絡架構時使用。當用戶提到等變層、G-CNN、e3nn、可操縱網絡、在模型中構建對稱性或需要特定對稱組的架構建議時調用。提供架構模式和實施指南。 來源：lyndonkl/claude。

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