Abstract: Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have ...

This paper characterizes the optimal taxation of top earners in a world with externalities. It takes a reduced-form approach that spans a broad class of models where top earners create externalities ...

Abstract: Recently, self-supervised learning has shown great potential in Graph Neural Networks (GNNs) through contrastive learning, which aims to learn discriminative features for each node without ...

When Chase Johnson was 31, her dog began acting strange. He was anxious, wouldn’t leave her side and, one day, pushed his nose into the side of her breast. Johnson felt a hard lump. “I wasn’t someone ...