Deep Tabular Learning
Value Imputation and Mask Estimation
Introduced by Yoon et al. in VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular DomainVIME , or Value Imputation and Mask Estimation, is a self- and semi-supervised learning framework for tabular data. It consists of a pretext task of estimating mask vectors from corrupted tabular data in addition to the reconstruction pretext task for self-supervised learning.
Source: VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
