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 41 0 0 26 Mar 2025
TAEGAN: Generating Synthetic Tabular Data For Data Augmentation Jiayu Li Zilong Zhao Kevin Yee Uzair Javaid Biplab Sikdar LMTD 29 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 33 5 0 24 Sep 2024
CTSyn: A Foundational Model for Cross Tabular Data Generation Xiaofeng Lin Chenheng Xu Matthew Yang Guang Cheng 39 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 Lió M. Jamnik LMTD 41 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 32 1 0 31 May 2024
STaSy: Score-based Tabular data Synthesis Jayoung Kim C. Lee Noseong Park DiffM 54 59 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 84 605 0 13 Mar 2020
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,244 0 09 Jun 2011