BMTI estimates log-density via integration of neighbor differences on data manifolds using maximum-likelihood weighting, without binning or explicit coordinates.
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A spectral-based GCN for directed graphs uses redefined Laplacians to enable direct application to directed data and outperforms prior methods on semi-supervised node classification tasks.
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Density Estimation via Binless Multidimensional Integration
BMTI estimates log-density via integration of neighbor differences on data manifolds using maximum-likelihood weighting, without binning or explicit coordinates.
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Spectral-based Graph Convolutional Network for Directed Graphs
A spectral-based GCN for directed graphs uses redefined Laplacians to enable direct application to directed data and outperforms prior methods on semi-supervised node classification tasks.