SOTAVerified

Synthetic Data Generation

The generation of tabular data by any means possible.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–625 of 822 papers

TitleStatusHype
Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation—0
Data-Driven Breakthroughs and Future Directions in AI Infrastructure: A Comprehensive Review—0
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders—0
Decentralised, Scalable and Privacy-Preserving Synthetic Data Generation—0
Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis—0
Deep learning based on Transformer architecture for power system short-term voltage stability assessment with class imbalance—0
Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure—0
deepNIR: Datasets for generating synthetic NIR images and improved fruit detection system using deep learning techniques—0
Demystifying Graph Neural Network Explanations—0
DepthSynth: Real-Time Realistic Synthetic Data Generation from CAD Models for 2.5D Recognition—0
DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis—0
Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN—0
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model—0
Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images—0
Detecting Anomalous Invoice Line Items in the Legal Case Lifecycle—0
Detecting Independent Pronoun Bias with Partially-Synthetic Data Generation—0
Differentially Private Federated Learning of Diffusion Models for Synthetic Tabular Data Generation—0
Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees—0
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation—0
Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders—0
Differentially Private Synthetic Data Using KD-Trees—0
Differentially Private Synthetic High-dimensional Tabular Stream—0
Differential Privacy Under Class Imbalance: Methods and Empirical Insights—0
DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection—0
DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models—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