Abstract: Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have ...
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 ...
Do you often replay the bad yet always forget the good? Here’s the science behind negative thought spirals and how to find balance and resilience. Do you know why our brains can replay our most ...
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