Abstract: Inspired by the impressive success of contrastive learning (CL), a variety of graph augmentation strategies have been employed to learn node representations in a self-supervised manner.

In this second part of the D315 direct start conversion for the Caterpillar D4, we continue the process of upgrading and modifying the system for smoother, more efficient operation. Watch as we ...

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 ...

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