An Efficient Architecture for Graph Problems [Paper] (VLDB 2022) ByteGNN: Efficient Graph Neural Network Training at Large Scale [Paper] (CIKM 2022) AdaGCL: Adaptive Subgraph Contrastive Learning to ...

In this paper, we present DynaGraph, a system that supports dynamic Graph Neural Networks (GNNs) efficiently. Based on the observation that existing proposals for dynamic GNN architectures combine ...

Abstract: This paper focuses on developing a performance guaranteed state estimation algorithm for 2D pose graph problems for mobile robots. Different from probabilistic methods, the measurement ...