3 papers
astro-ph.HE2026
Testing the Generalization and Domain Stability of Compact Feature Representations for Photometric Supernova Classification
Anurag Garg
Photometric classification of supernovae increasingly requires models that are not only accurate within a single survey but also robust to changes in cadence, noise properties, fil…
cs.LG2026
TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
Léo Grinsztajn, Klemens Flöge, Oscar Key +23
The first tabular foundation model, TabPFN, and its successor TabPFNv2 have impacted tabular AI substantially, with dozens of methods building on it and hundreds of applications ac…
cs.LG2025
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
Anurag Garg, Muhammad Ali, Noah Hollmann +3
Foundation models for tabular data, like TabPFN, achieve strong performance on small datasets when pre-trained solely on synthetic data. We show that this performance can be signif…