面向几何图的新型Clifford Sheaf神经网络架构介绍

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 04:00

研究人员介绍了一种新颖的Clifford Sheaf神经网络（CSNN）架构，该架构专为几何图设计。该网络将Clifford代数融入细胞束的每个茎中，从而能够跨边传输多向量特征。CSNN使用“K项三明治”机制进行限制映射，该机制允许进行等级混合，并通过构造确保了束拉普拉斯算子是半正定的。这种方法比传统的向量共轭等方法具有更高的表达能力，特别适用于图级等变回归任务。 AI

影响介绍了一种用于几何图的新型神经网络架构，有望推动等变深度学习的研究。

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arXiv stat.ML TIER_1 English(EN) · Kotaro Kamiya, Joel Nicholls · 2026-10-02 04:00

Clifford Sheaf Neural Networks

arXiv:2610.01322v1 Announce Type: cross Abstract: We introduce the Clifford Sheaf Neural Network (CSNN), an equivariant sheaf neural network for geometric graphs that places a Clifford algebra on each stalk of a cellular sheaf and transports multivector features along edges. The …

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Clifford Sheaf Neural Networks

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