Node Classification
PulseAugur coverage of Node Classification — every cluster mentioning Node Classification across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New nonlinear Laplacian operator enhances graph neural networks for signed-directed data
Researchers have developed a new non-linear Laplacian operator, termed NLSD, specifically designed for signed-directed graphs. This operator extends existing concepts for signed and directed graphs by calculating node-s…
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New protocol for GNN cross-task transfer reveals directional predictability
Researchers have developed a new protocol to reliably evaluate cross-task transfer in Graph Neural Networks (GNNs) for node classification (NC) and link prediction (LP) tasks. Their findings indicate that transfer from …
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Study questions effectiveness of heterogeneous graph neural networks for node classification
A new study published on arXiv investigates the effectiveness of heterogeneous graph neural networks (HGNNs) for node classification. Researchers conducted extensive reproductions across 21 datasets and 20 baseline mode…
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Aitchison geometry powers new compositional graph embeddings and flavor tagger calibration
Two new arXiv papers introduce novel approaches to representation learning using Aitchison geometry. One paper proposes a framework for calibrating flavor taggers in high-energy physics by formulating it as an optimal t…