On the Usefulness of Synthetic Tabular Data Generation

27 June 2023

Papers citing "On the Usefulness of Synthetic Tabular Data Generation"

9 / 9 papers shown

Title
Assessing Generative Models for Structured Data Reilly Cannon Nicolette M. Laird Caesar Vazquez Andy Lin Amy Wagler Tony Chiang 43 0 0 26 Mar 2025
TAEGAN: Generating Synthetic Tabular Data For Data Augmentation Jiayu Li Zilong Zhao Kevin Yee Uzair Javaid Biplab Sikdar LMTD 45 1 0 02 Oct 2024
TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models Andrei Margeloiu Xiangjian Jiang Nikola Simidjievski M. Jamnik 43 5 0 24 Sep 2024
CTSyn: A Foundational Model for Cross Tabular Data Generation Xiaofeng Lin Chenheng Xu Matthew Yang Guang Cheng 43 3 0 07 Jun 2024
TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting Andrei Margeloiu A. Bazaga Nikola Simidjievski Pietro Lio M. Jamnik LMTD 59 5 0 03 Jun 2024
Navigating Tabular Data Synthesis Research: Understanding User Needs and Tool Capabilities Maria F. Davila Sven Groen Fabian Panse Wolfram Wingerath LMTD 39 1 0 31 May 2024
STaSy: Score-based Tabular data Synthesis Jayoung Kim C. Lee Noseong Park DiffM 62 60 0 08 Oct 2022
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data Nick Erickson Jonas W. Mueller Alexander Shirkov Hang Zhang Pedro Larroy Mu Li Alex Smola LMTD 97 612 0 13 Mar 2020
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,308 0 09 Jun 2011