Abstract: Graph neural networks (GNNs) that collect information from neighbors are commonly utilized in semi-supervised learning contexts. In particular, a significant body of research has been ...
Abstract: Self-supervised graph embedding has emerged as a powerful paradigm for learning expressive node and graph representations without relying on real labels. Several recent self-supervised ...
FastNoise2 is built around a node graph architecture. Rather than calling standalone functions to generate noise, you build a tree of interconnected nodes, then evaluate the root node to get the final ...
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