In this video, I summarize the different transformations you can apply to a graph, specifically focusing on how they impact a ...

In this math tutorial, we compare and contrast four different transformations for the absolute value function. We'll look at ...

Abstract: We present the Topology Transformation Equivariant Representation learning, a general paradigm of self-supervised learning for node representations of graph data to enable the wide ...

Abstract: Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost.