Unfolding the Meandering Path: High-Dimensional Invariance and the Flat 2D Plane of Neural…
中文摘要
本文探讨神经网络的高维不变性，揭示复杂数据如何映射到二维平面，以深入理解模型的内部表征与几何结构。
English Summary
This article explores high-dimensional invariance in neural networks, demonstrating how complex data structures map to a flat 2D plane to reveal underlying internal representations and geometry.
原文节选
Author: Supat Charoensappuech, in collaboration with Gemini 3.5 Flash (in normal mode Continue reading on Medium »