2022 Workshop Proceedings

Individual Files



Day One

Day Two




  • On the Relationship between Heterophily and Robustness of Graph Neural Networks - Jiong Zhu (link to file)
  • GXAI-Bench: Evaluating Explainers for Graph Machine Learning Algorithms - Owen Queen (link to file)
  • Explaining Graph Embeddings - Zohair Shafi (link to part 1) (link to part 2)
  • Defense Against Shortest Path Attacks - Ben Miller (link to part 1) (link to part 2)
  • Fast and Scalable Graph Neural Networks with PyTorch + SALIENT - Tim Kaler (link to part 1) (link to part 2)
  • Understanding Graph Neural Network Fairness in the Presence of Heterophilic Neighborhoods - Donald Loveland (link to file)
  • Exploring Materials Surfaces with Deep Learning for CO2 Reduction - Xiaochen Du (link to file)
  • Factorization-Based Deep Generative Models for Graphs - William Shiao (link to file)