Dataset Groups Activity Stream Inductive Matrix Completion Using Graph Autoencoder Matrix completion has been formulated as the link prediction problem on a bipartite user-item graph in recent GNN-based matrix completion methods. BibTex: @dataset{Wei_Shen_and_Chuheng_Zhang_and_Yun_Tian_and_Liang_Zeng_and_Xiaonan_He_and_Wanchun_Dou_and_Xiaolong_Xu_2024, abstract = {Matrix completion has been formulated as the link prediction problem on a bipartite user-item graph in recent GNN-based matrix completion methods.}, author = {Wei Shen and Chuheng Zhang and Yun Tian and Liang Zeng and Xiaonan He and Wanchun Dou and Xiaolong Xu}, doi = {10.57702/nim59ts8}, institution = {No Organization}, keyword = {'Graph Neural Networks', 'Inductive Learning', 'Matrix Completion', 'Recommender Systems'}, month = {dec}, publisher = {TIB}, title = {Inductive Matrix Completion Using Graph Autoencoder}, url = {https://service.tib.eu/ldmservice/dataset/inductive-matrix-completion-using-graph-autoencoder}, year = {2024} }
