Author

Malena Loza

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Preprint Aug 2026

Test-Time Augmentation for Tabular-to-Image Classifiers under Distribution Shifts

Results indicate that TTA improves OOD performance, with composite and photometric strategies providing the best trade-off between robustness and variance, in contrast to frequency-domain transformations that alter the encoder's feature-to-intensity mapping consistently degrade performance.

Malena Loza, Felipe Grijalva, Eva Milara et al. · 0 citations

Preprint Jul 2026

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

Existing benchmarks for OOD in tabular data are extended, providing evidence to support their adoption in high-stakes domains characterized by structural distribution shifts and identifying a scalability gap.

Malena Loza, David Chushig-Muzo, Eva Milara et al. · 0 citations