Framework for understanding when architectural modularity matters in continual learning based on representational dimensionality. Shows that modular networks only outperform monolithic ones in low-dimensional regimes where representational geometry is constrained. Triggers: continual learning dimensionality, modular vs monolithic networks, representational geometry, stability-plasticity tradeoff,
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Type: Agent skill (SKILL.md) · Category: Maps, Travel & Location · Source: https://github.com/hiyenwong/ai_collection/tree/HEAD/collection/skills/ai-ml/dim
| Capabilities (fewer powerful permissions = higher) | 50/50 |
| Maintenance | 21/35 |
| Documentation | 15/15 |
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