Post #198

Fresh picks from ArXiv This week we have papers on theory of GNN, their applications to recommendation and other fields, a historical reference on available graph repositories, and a discussion of peer review vs biblio metrics to assess scientific performance 👨‍⚖️ GNN • Characterizing the Expressive Power of Invariant and Equivariant Graph Neural Networks • Building powerful and equivariant graph neural networks with message-passing with Andreas Loukas • Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case ICML 2020 Applications • Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters • Scalable Deep Generative Modeling for Sparse Graphs with Yujia Li, ICML 2020 • GPT-GNN: Generative Pre-Training of Graph Neural Networks KDD 2020 • Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits Graph Problems • Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View with Philip S. Yu • Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework with Mikhail Galkin • Graph Policy Network for Transferable Active Learning on Graphs with Jian Tang • Online Dense Subgraph Discovery via Blurred-Graph Feedback with Masashi Sugiyama, ICML 2020 Surveys • A survey of repositories in graph theory • Metrics and peer review agreement at the institutional level