Summary of Learning to Control the Smoothness Of Graph Convolutional Network Features, by Shih-hsin Wang et al.
Learning to Control the Smoothness of Graph Convolutional Network Featuresby Shih-Hsin Wang, Justin Baker, Cory…
Learning to Control the Smoothness of Graph Convolutional Network Featuresby Shih-Hsin Wang, Justin Baker, Cory…
Partially Trained Graph Convolutional Networks Resist Oversmoothingby Dimitrios Kelesis, Dimitris Fotakis, Georgios PaliourasFirst submitted to…
KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Predictionby Longlong Li, Yipeng Zhang, Guanghui Wang,…
PromptGCN: Bridging Subgraph Gaps in Lightweight GCNsby Shengwei Ji, Yujie Tian, Fei Liu, Xinlu Li,…
Text Classification using Graph Convolutional Networks: A Comprehensive Surveyby Syed Mustafa Haider Rizvi, Ramsha Imran,…
Evaluating the effects of Data Sparsity on the Link-level Bicycling Volume Estimation: A Graph Convolutional…
Graph Network Models To Detect Illicit Transactions In Block Chainby Hrushyang Adloori, Vaishnavi Dasanapu, Abhijith…
Labor Migration Modeling through Large-scale Job Query Databy Zhuoning Guo, Le Zhang, Hengshu Zhu, Weijia…
Benchmarking Reliability of Deep Learning Models for Pathological Gait Classificationby Abhishek Jaiswal, Nisheeth SrivastavaFirst submitted…
Graph Similarity Regularized Softmax for Semi-Supervised Node Classificationby Yiming Yang, Jun Liu, Wei WanFirst submitted…