3 citations · 3 across the 3 of their papers we have counts for
4 papers
Advancing Open and Reproducible Relational Learning: RelArena-, TabPFN-Rel and RPI
Adrian Hayler, Klemens Flöge, Alan Arazi +44
This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we expect to accelerate researc…
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…
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…
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…