8 citations · 19 across the 4 of their papers we have counts for
3 papers · 1 filter
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces
Max Zhu, Katarzyna Kobalczyk, Andrija Petrovic +4
Despite the prevalence of tabular datasets, few-shot learning remains under-explored within this domain. Existing few-shot methods are not directly applicable to tabular datasets d…
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark
Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar +1
Synthetic data serves as an alternative in training machine learning models, particularly when real-world data is limited or inaccessible. However, ensuring that synthetic data mir…
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models
Aleksa Bisercic, Mladen Nikolic, Mihaela van der Schaar +3
Tabular data is often hidden in text, particularly in medical diagnostic reports. Traditional machine learning (ML) models designed to work with tabular data, cannot effectively pr…