Representation Learning on Heterostructures via Heterogeneous Anonymous Walks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3234005
Abstract: Capturing structural similarity has been a hot topic in the field of network embedding (NE) recently due to its great help in understanding node functions and behaviors. However, existing works have paid very much attention… read more here.
Keywords: heterogeneous anonymous; via heterogeneous; representation learning; heterostructures via ... See more keywords