most citedMultivariate Feature Selection and Autoencoder Embeddings of Ovarian Cancer Clinical and Genetic Data

15 citations · 27 across the 5 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…

cs.LG2025★ 15 cited

Multivariate Feature Selection and Autoencoder Embeddings of Ovarian Cancer Clinical and Genetic Data

Luis Bote-Curiel, Sergio Ruiz-Llorente, Sergio Muñoz-Romero +4

This study explores a data-driven approach to discovering novel clinical and genetic markers in ovarian cancer (OC). Two main analyses were performed: (1) a nonlinear examination o…