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May, 2023
图神经网络与三维拓扑
Graph Neural Networks and 3-Dimensional Topology
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Pavel Putrov, Song Jin Ri
TL;DR
本研究测试应用几何深度学习到低维拓扑问题的效果，在一个简单的模型中，使用图神经网络来判断一对图是否给出同构三维多样体，通过监督学习和强化学习来训练和优化神经网络模型的准确率和效率。
Abstract
We test the efficiency of applying
geometric deep learning
to the problems in
low-dimensional topology
in a certain simple setting. Specifically, we consider the class of 3-manifolds described by plumbing graphs
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