Graph Learning

• The Flowing Nature Matters: Feature Learning from the Control Flow Graph of Source Code for Bug Localization
  Yi-Fan Ma (Nanjing University)*; Ming Li (Nanjing University)
• DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks
  Rahul Kukreja (IIITD); Ansh Kumar Sharma (IIITD); Ranjitha Prasad (IIIT Delhi)*; Shilpa Rao (IIIT Guwahati)
• Quaternion Graph Neural Networks
  Dai Quoc Nguyen (Monash University)*; Tu Dinh Nguyen (VinAI Research); Dinh Phung (Monash University)
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• Convolutional Hypercomplex Embeddings for Link Prediction
  Caglar Demir (Paderborn University)*; Diego Moussallem (Paderborn Univerisity); Stefan Heindorf (Paderborn University); Axel-Cyrille Ngonga Ngomo (Paderborn University)
• Metric Learning for comparison of HMMs using Graph Neural Networks
  rajan kumar soni (Indian Institute of technology, madras)*; Karthick Seshadri (NIT Andhra Pradesh); Balaraman Ravindran (Indian Institute of Technology, Madras)
• Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks
  Shibo Yao (New Jersey Institute of Technology)*; Dantong Yu (New Jersey Institute of Technology); XIANGMIN JIAO (Stony Brook University)
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• Bayesian neural network unit priors and generalized Weibull-tail property
  Mariia Vladimirova (Inria Grenoble Rhone-Alpes)*; Julyan Arbel (Inria Grenoble Rhone-Alpes); Stephane Girard (INRIA)