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cs.LG2023
Unifying gradient regularization for Heterogeneous Graph Neural Networks
Xiao Yang, Xuejiao Zhao, Zhiqi Shen
Heterogeneous Graph Neural Networks (HGNNs) are a class of powerful deep learning methods widely used to learn representations of heterogeneous graphs. Despite the fast development…
cs.LG2017★ 1 cited
Learning non-parametric Markov networks with mutual information
Janne Leppä-aho, Santeri Räisänen, Xiao Yang +1
We propose a method for learning Markov network structures for continuous data without invoking any assumptions about the distribution of the variables. The method makes use of pre…