Graphs are a representation of structured data that captures the
relatio...
Despite a surge in interest in GNN development, homogeneity in benchmark...
Unsupervised learning has recently significantly gained in popularity,
e...
Personalized PageRank (PPR) is a fundamental tool in unsupervised learni...
Representative selection (RS) is the problem of finding a small subset o...
Graph learning algorithms have attained state-of-the-art performance on ...
Despite advances in the field of Graph Neural Networks (GNNs), only a sm...
What is the best way to match the nodes of two graphs? This graph alignm...
In this paper, we introduce InstantEmbedding, an efficient method for
ge...
Graph Neural Networks (GNNs) have achieved state-of-the-art results on m...
Low-dimensional representations, or embeddings, of a graph's nodes facil...
Graph comparison is a fundamental operation in data mining and informati...
Generative models are often used to sample high-dimensional data points ...
Representing a graph as a vector is a challenging task; ideally, the
rep...
Embedding a web-scale information network into a low-dimensional vector ...