BriefGPT.xyz
May, 2024
对不变性学习和等变性学习的正式观点
A Canonization Perspective on Invariant and Equivariant Learning
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George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
TL;DR
利用框架取代方法来实现神经网络的对称性,引入了规范化角度,设计了对特征向量更优且理论上和实践中都更优的新框架,揭示了现有方法之间的等价性。
Abstract
In many applications, we desire
neural networks
to exhibit invariance or equivariance to certain groups due to symmetries inherent in the data. Recently,
frame-averaging methods
emerged to be a unified framework
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