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Session 6E: Performance and Temporality issues in Graph Neural Networks

First presentation

Chair: Lun Du

Start: 2021-11-04 13:00

End: 2021-11-04 14:10

Second presentation

Chair: Shoaib Jameel

Start: 2021-11-05 01:00

End: 2021-11-05 02:10

Papers in this session

rgfp1533 Node2Grids: A Cost-Efficient Uncoupled Training Framework for Large-Scale Graph Learning

afp1006 Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

rgfp1481 Understanding and Resolving Performance Degradation in Deep Graph Convolutional Networks

rgfp0521 Cache-based GNN System for Dynamic Graphs

rgfp0115 LiteGT: Efficient and Lightweight Graph Transformers

rgfp0848 Fast k-NN Graph Construction by GPU based NN-Descent

rgfp1059 iMap: Incremental Node Mapping between Large Graphs Using GNN

rgfp1203 Contrastive Pre-Training of GNNs on Heterogeneous Graphs

rgfp1473 Rectifying Pseudo Labels: Iterative Feature Clustering for Graph Representation Learning

Papers highlighted in green indicate the paper is selected for a live spotlight presentation.
Papers highlighted in gold indicate the paper has been shortlisted for a best paper award (and will also be presented live).

This programme is indicative. Once registered, please refer to the session programme on Underline.