3 papers
cs.CV2026
TabSOM: A tabular-to-image encoding method based on self-organizing maps
David Chushig-Muzo, María Ángeles Rodríguez de Cara, Eva Milara +3
Tabular-to-image methods have emerged as novel approaches to leverage the high predictive performance of convolutional neural networks and vision transformers. They convert tabular…
cs.CV2026
Test-Time Augmentation for Tabular-to-Image Classifiers under Distribution Shifts
Malena Loza, Felipe Grijalva, Eva Milara +3
Tabular-to-image methods that convert tabular data into visual representations have emerged as a novel paradigm for leveraging the high performance of deep learning models. Despite…
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…