Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark

25 October 2023

Papers citing "Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark"

20 / 20 papers shown

Title
A Comprehensive Survey of Synthetic Tabular Data Generation Ruxue Shi Yili Wang Mengnan Du Xu Shen Xin Wang 210 2 0 23 Apr 2025
Targeted synthetic data generation for tabular data via hardness characterization Tommaso Ferracci Leonie Goldmann Anton Hinel Francesco Sanna Passino 225 0 0 01 Oct 2024
A Study on Improving Realism of Synthetic Data for Machine Learning Ting-Li Shen Ganning Zhao Suya You GAN 37 6 0 24 Apr 2023
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data Nabeel Seedat Jonathan Crabbé Ioana Bica M. Schaar 62 25 0 24 Oct 2022
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 81 368 0 18 Jul 2022
Data-SUITE: Data-centric identification of in-distribution incongruous examples Nabeel Seedat Jonathan Crabbé Mihaela van der Schaar OOD 57 14 0 17 Feb 2022
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 112 687 0 05 Oct 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 91 58 0 23 Sep 2021
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data Hari Prasanna Das Ryan Tran Japjot Singh Xiangyu Yue G. Tison Alberto L. Sangiovanni-Vincentelli C. Spanos OOD MedIm 114 52 0 14 Sep 2021
MLReal: Bridging the gap between training on synthetic data and real data applications in machine learning T. Alkhalifah Hanchen Wang O. Ovcharenko OOD 75 68 0 11 Sep 2021
Data Quality Toolkit: Automatic assessment of data quality and remediation for machine learning datasets Nitin Gupta Hima Patel S. Afzal Naveen Panwar Ruhi Sharma Mittal ... S. Mehta Sandeep Hans P. Lohia Aniya Aggarwal Diptikalyan Saha 63 41 0 12 Aug 2021
Tabular Data: Deep Learning is Not All You Need Ravid Shwartz-Ziv Amitai Armon LMTD 159 1,265 0 06 Jun 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 98 500 0 08 Mar 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 89 197 0 17 Feb 2021
A Data Quality-Driven View of MLOps Cédric Renggli Luka Rimanic Nezihe Merve Gürel Bojan Karlavs Wentao Wu Ce Zhang AI4TS 44 65 0 15 Feb 2021
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 149 692 0 31 Oct 2019
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 663 5,808 0 25 Jul 2019
Modeling Tabular data using Conditional GAN Lei Xu Maria Skoularidou Alfredo Cuesta-Infante K. Veeramachaneni CML MU SyDa GAN 116 1,255 0 01 Jul 2019
Measuring the quality of Synthetic data for use in competitions James Jordon Jinsung Yoon M. Schaar 44 32 0 29 Jun 2018
Data Augmentation Generative Adversarial Networks Antreas Antoniou Amos Storkey Harrison Edwards MedIm GAN 135 1,071 0 12 Nov 2017