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…
Graph Similarity Regularized Softmax for Semi-Supervised Node Classificationby Yiming Yang, Jun Liu, Wei WanFirst submitted…
Benchmarking Reliability of Deep Learning Models for Pathological Gait Classificationby Abhishek Jaiswal, Nisheeth SrivastavaFirst submitted…