A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as gr...

書目詳細資料
發表在:	Axioms
Main Authors:	Roy T. Forestano, Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
格式:	Article
語言:	英语
出版:	MDPI AG 2024-02-01
主題:	quantum computing deep learning quantum machine learning equivariance invariance supervised learning
在線閱讀:	https://www.mdpi.com/2075-1680/13/3/160

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