SOTAVerified

Synthetic Data Generation

The generation of tabular data by any means possible.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 726–750 of 822 papers

TitleStatusHype
Synthetic Data Generation for Fraud Detection using GANs—0
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data—0
Generation of Synthetic Electronic Health Records Using a Federated GAN—0
CDCGen: Cross-Domain Conditional Generation via Normalizing Flows and Adversarial Training—0
WeChat Neural Machine Translation Systems for WMT21—0
Data-driven modeling of time-domain induced polarizationCode0
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages—0
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation—0
SimDem A Multi-agent Simulation Environment to Model Persons with Dementia and their Assistance—0
Virtual Temporal Samples for Recurrent Neural Networks: applied to semantic segmentation in agriculture—0
Universum GANs: Improving GANs through contradictions—0
An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises—0
Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking—0
Iterative Methods for Private Synthetic Data: Unifying Framework and New MethodsCode0
Tensor feature hallucination for few-shot learningCode0
Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans—0
Content Disentanglement for Semantically Consistent Synthetic-to-Real Domain AdaptationCode0
Towards Synthetic Multivariate Time Series Generation for Flare Forecasting—0
Adapting deep generative approaches for getting synthetic data with realistic marginal distributions—0
Transitioning from Real to Synthetic data: Quantifying the bias in model—0
Synthetic Data for Model Selection—0
Causal-TGAN: Generating Tabular Data Using Causal Generative Adversarial Networks—0
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performance—0
Adaptation of Back-translation to Automatic Post-Editing for Synthetic Data GenerationCode0
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation—0
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All datasetsUCI Epileptic Seizure RecognitionUNSW-NB15

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1corGANAUROC0.92—Unverified
2GANAUROC0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1kiNETGANEMD0.07—Unverified
2CTGANEMD0.07—Unverified