A systematic framework modularizes tabular data disentanglement into data extraction, modeling, analysis, and latent extrapolation, with a case study on synthetic data generation.
Subtab: Subsetting fea- tures of tabular data for self-supervised representation learning.Advances in Neural Information Processing Systems, 34:18853–18865, 2021
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A Systematic Framework for Tabular Data Disentanglement
A systematic framework modularizes tabular data disentanglement into data extraction, modeling, analysis, and latent extrapolation, with a case study on synthetic data generation.