GitHub

GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

We conduct the experiments on a Linux server with an Intel Xeon Gold 6226R CPU and two Tesla V100S GPUs. We implement our method with PyTorch 1.11.0 and Pytorch Geometric 2.0.4.
IEEE

Deep Graph Convolutional Autoencoder With Conditional Normalizing Flow for Power Distribution Systems Fault Classification and Location

Abstract: Accurate fault classification and location are critical to ensure the reliability and resilience of large-scale power distribution systems (PDSs). The existing data-driven works in this area ...
IEEE

GI-Graph: A Generative Invariant Graph Learning Scheme Towards Out-of-Distribution Generalization

Abstract: When distribution shifts occur between testing and training graph data, out-of-distribution (OOD) samples undermine the performance of graph neural networks (GNNs). To improve adaptive OOD ...