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...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Axioms
المؤلفون الرئيسيون: 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
التنسيق: مقال
اللغة:الإنجليزية
منشور في: MDPI AG 2024-02-01
الموضوعات:
quantum computing
deep learning
quantum machine learning
equivariance
invariance
supervised learning
الوصول للمادة أونلاين:https://www.mdpi.com/2075-1680/13/3/160

الانترنت

https://www.mdpi.com/2075-1680/13/3/160

مواد مشابهة