most citedLM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks

3 citations · 3 across the 4 of their papers we have counts for

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cs.LG2026

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

Malena Loza, David Chushig-Muzo, Eva Milara +3

Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to ensemble tree-based models. Most…