Inductive Matrix Completion Based on Graph Neural Networks

26 April 2019

Papers citing "Inductive Matrix Completion Based on Graph Neural Networks"

9 / 9 papers shown

Title
Deep Generative Models for Subgraph Prediction Erfaneh Mahmoudzadeh Parmis Naddaf Kiarash Zahirnia Oliver Schulte BDL GNN 21 0 0 07 Aug 2024
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures Tianyi Zhang Haoteng Yin Rongzhe Wei Pan Li Anshumali Shrivastava AI4CE 18 1 0 28 Dec 2023
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning Jing Zhu Xiang Song V. Ioannidis Danai Koutra Christos Faloutsos 41 13 0 25 Sep 2023
Item Graph Convolution Collaborative Filtering for Inductive Recommendations Edoardo DÁmico Khalil Muhammad E. Tragos Barry Smyth N. Hurley A. Lawlor GNN 11 6 0 28 Mar 2023
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning Haoteng Yin Muhan Zhang Jianguo Wang Pan Li 61 8 0 06 Mar 2023
Predicting Molecule-Target Interaction by Learning Biomedical Network and Molecule Representations Jinjiang Guo Jie Li 8 0 0 02 Feb 2023
Interpreting the Mechanism of Synergism for Drug Combinations Using Attention-Based Hierarchical Graph Pooling Zehao Dong Heming Zhang Yixin Chen Philip R. O. Payne Fuhai Li GNN 27 16 0 19 Sep 2022
Bipartite Graph Embedding via Mutual Information Maximization Jiangxia Cao Xixun Lin Shu Guo Luchen Liu Tingwen Liu Bin Wang 67 110 0 10 Dec 2020
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs Muhan Zhang Shali Jiang Zhicheng Cui Roman Garnett Yixin Chen GNN BDL CML 6 196 0 24 Apr 2019