GitHub

(ICLR 2024 Oral) Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space

[2024-06-20]: Disable loading irrelvent packages when training individual models; update the instruction for DCR experiements; fix minor bugs in TabSyn's training script. [2024-05-14]: Add demo code ...
IEEE

An Interpretable Adaptive Multiscale Attention Deep Neural Network for Tabular Data

Abstract: Deep learning (DL) has been demonstrated to be a valuable tool for analyzing signals such as sounds and images, thanks to its capabilities of automatically extracting relevant patterns as ...
IEEE

A Universal Metric for Robust Evaluation of Synthetic Tabular Data

Abstract: Synthetic tabular data generation becomes crucial when real data are limited, expensive to collect, or simply cannot be used due to privacy concerns. However, producing good quality ...
GitHub

TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling" (ICLR 2025)

This is the official repository of the paper "TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling". It consists of two parts: One dot represents a performance score on one ...