IEEE

Tabular Data Classification and Regression: XGBoost or Deep Learning With Retrieval-Augmented Generation

Abstract: Tabular data is the most prevalent form of structured data, necessitating robust models for classification and regression tasks. Traditional models like eXtreme Gradient Boosting (XGBoost) ...
GitHub

TabPFGen: Synthetic Tabular Data Generation with TabPFN

TabPFGen is a Python library for generating high-quality synthetic tabular data using energy-based modeling and stochastic gradient Langevin dynamics (SGLD). It supports both classification and ...
GitHub

Graph Neural Networks for Tabular Data Learning (GNN4TDL)

The deep learning-based approaches to Tabular Data Learning (TDL), classification and regression, have shown competing performance, compared to their conventional counterparts. However, the latent ...
IEEE

Utility Meets Privacy: A Critical Evaluation of Tabular Data Synthesizers

Abstract: Evaluating synthetic data requires careful consideration of both utility and privacy. This study analyzes 12 synthesizers across 17 tabular health datasets, providing large-scale, comparable ...