Abstract: Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity and can only handle graphs with at most thousands of nodes. To this ...

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...

pyiron_workflow is a framework for constructing workflows as computational graphs from simple python functions. Its objective is to make it as easy as possible to create reliable, reusable, and ...

In one of the largest democracies of the world-India- evaluating a year gone-by is as complex as the multi-religion complexities and the Hindu caste system. When the state or the ruling dispensation ...

Recent augmentation-based methods showed that message-passing (MP) neural networks often perform poorly on low-degree nodes, leading to degree biases due to a lack of messages reaching low-degree ...