TabKDE generates synthetic tabular data using copula transformations followed by kernel density estimation, matching prior accuracy with negligible training time and reduced storage via coresets.
Learning a Mahalanobis distance metric for data clustering and classification
2 Pith papers cite this work. Polarity classification is still indexing.
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Two-stage GMM clustering of close-in exoplanets in dynamical feature space mapped to pebble-accretion models identifies sub-populations with distinct formation histories including earlier epochs for very-massive gas giants.
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TabKDE: Simple and Scalable Tabular Data Generation with Kernel Density Estimates
TabKDE generates synthetic tabular data using copula transformations followed by kernel density estimation, matching prior accuracy with negligible training time and reduced storage via coresets.
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Machine-learning clustering of close-in exoplanet populations: links to pebble accretion
Two-stage GMM clustering of close-in exoplanets in dynamical feature space mapped to pebble-accretion models identifies sub-populations with distinct formation histories including earlier epochs for very-massive gas giants.