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Synthetic Data356 papers Synthetic Data233 papers Synthetic Data Augmentation155 papers Synthetic Dataset53 papers Synthetic Tabular Data42 papers Synthetic Training Data33 papers

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Papers

Boosting ECG Classification Performance by Pre-training with Synthesized Data
Jun 9, 2026Naoki Nonaka, Jun SeitaElectrocardiogram Classification Pediatric-Adult Electrocardiogram Alignment
Generative Synthetic Data for Causal Inference: Pitfalls, Remedies, and Opportunities
Apr 26, 2026Yichen XuCausal Inferences Synthetic Data
When Does Generating More Help? Disentangling Fixed-Source Synthesis from Source Expansion in Synthetic Data Scaling
Jul 2, 2026Xu Guo, Jian Tong, Zhihui Lu +1Synthetic Data Automated Synthesis Techniques
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Feb 3, 2026Vignesh Kothapalli, Rishabh Ranjan, Valter Hudovernik +4Relational Deep Learning Synthetic Data
SoK: Reconstruction Attacks on Synthetic Tabular Data (Insights from Winning the NIST CRC)
Jun 6, 2026Steven Golob, Sikha Pentyala, Martine De CockSynthetic Tabular Data Privacy-Preserving Framework
Where to Intervene? Benchmarking Fairness-Aware Learning on Differentially Private Synthetic Tabular Data
Jul 8, 2026Vinícius Gabriel Angelozzi, Héber H. ArcoleziDifferential Privacy Fairness-Aware Learning
Learning from Many Voices: Literary MT Using Multi-Reference Human and Synthetic Data
Dec 24, 2024Si Wu, John Wieting, David A. SmithMachine Translation Multimodal Dataset
PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization
Jun 16, 2026Arshia Ilaty, Hossein Shirazi, Manasi Chitale +5Synthetic Tabular Data Privacy-Preserving Framework
NeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation
Sep 15, 2026Johnny Greco, Nabin Mulepati, Andre Manoel +8Synthetic Data Multimodal Generation
Few-Shot Synthetic Data Generation with Diffusion Models for Downstream Vision Tasks
May 12, 2026Daniil Dushenev, Nazariy Karpov, Daniil Zinovjev +2Synthetic Data Medical Image Generation
Trustworthy synthetic data for campaign decision support: strategy simulation fidelity and the PolicySynth framework
Jul 13, 2026Tung Dang, The Hung Phung, Son Lam Nguyen +1Synthetic Data Decision Support
The Impact of Synthetic Data Augmentation on Discourse-Pragmatic Function Classification
Sep 3, 2026Sara Sorahi, Kevin Tang, Reza KazemianSynthetic Training Data Synthetic Data Augmentation
DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis
May 2, 2026Zhichao Shi, Cehao Yang, Hao Zhou +6Synthetic Data Multimodal Learning
Improving Low-Resolution Face Recognition under Limited Data: How Synthetic Data Generation Can Close the Domain Gap
Aug 6, 2026Luis S. Luevano, Ünsal Öztürk, Hatef Otroshi Shahreza +2Facial Recognition Synthetic-To-Real Domain Gap
Differentially Private Synthetic Data via APIs 4: Tabular Data
Jun 6, 2026Toan Tran, Arturs Backurs, Zinan Lin +3Synthetic Tabular Data Differential Privacy
Quantum-Enhanced Synthetic Data Generation Using Quantum Circuit Born Machines for Imbalanced Tabular Learning
Jul 10, 2026Tanapol Nuatho, Narisorn Sangnakara, Prapong Prechaprapranwong +1Oversampling Synthetic Data
Distillation of Synthetic Data for Time Series Foundation Models
Sep 9, 2026Niloy Biswas, Noureddine El KarouiTime Series Foundation Models Synthetic Data
Disparate Impact in Synthetic Data Generation
Jun 11, 2026Paul Andrey, Michaël Perrot, Batiste Le Bars +1Synthetic Data Differential Privacy
When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?
Jun 24, 2026Zhengchi Ma, Pengfei Lyu, Anru R. ZhangOversampling Class Imbalance
ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition
Jun 11, 2025Parsa Rahimi, Sebastien MarcelSynthetic Data Score-Based Diffusion Model
Generative Modeling of Complex-Valued Brain MRI Data
Apr 16, 2026Marco Schlimbach, Moritz Rempe, Jessica Mnischek +4Magnetic Resonance Imaging Medical Image Generation
How Far Can Synthetic Data Take Thai OCR?
Sep 3, 2026Kunat PipatanakulOptical Character Recognition Deepseek-Ocr
Fixed-Parameter Tractability of Private Synthetic Data Generation
Jun 9, 2026Badih Ghazi, Cristóbal Guzmán, Pritish Kamath +3Differential Privacy Synthetic Data
The Effects of Synthetic Data and Label Distribution on Canola Branch Counting
Jul 10, 2026Amirsalar Darvishpour, Mikolaj Cieslak, Adam RunionsSynthetic Dataset Synthetic-To-Real Domain Gap
Portable Causal Fairness Across Synthetic Data Generator Families
Sep 2, 2026Steven Golob, Sikha Pentyala, Martine De CockSynthetic Data Generators
NodeSynth: Socially Aligned Synthetic Data for AI Evaluation
May 14, 2026Qazi Mamunur Rashid, Xuan Yang, Zhengzhe Yang +5Synthetic Data Generative Artificial Intelligence
Beyond Pixel Similarity: Task-Aware Evaluation of GAN-Based Synthetic Sonar Data for Robotic Perception
Sep 16, 2026Hannan Ejaz Keen, Muhammad Moazam Fraz, Karsten BernsForward-Looking Sonar Synthetic Image Detection
It does what it says on the tin: safe synthetic data from coarsened margins
Jun 1, 2026Gillian M RaabSynthetic Data Covariate Shift
SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo
Apr 6, 2026Zeyu Ma, Alexander Raistrick, Jia DengMulti-View Synthetic Data
$S^3$ -R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data
May 2, 2026Harsh Goel, Akhil Udathu, Susmija Jabbireddy +2Multi-Hop Question Answering Benchmarks Sparse Rewards

Jun 9, 2026 · cs.LGJ/K move · Enter open · S save

Boosting ECG Classification Performance by Pre-training with Synthesized Data

Naoki Nonaka, Jun Seita

Advanced Data Science Project, RIKEN Information R&D and Strategy Headquarters

Deep Neural Networks (DNNs) typically require extensive datasets for effective training. In the medical domain, acquiring large-scale data is often challenging due to privacy concerns and the rarity of certain diseases. To address this data scarcity, we investigate the efficacy of training DNN models using synthetic data, generated based on domain-specific medical knowledge. Specifically, we develop a knowledge-driven Gaussian-composition synthesis algorithm for single-lead II ECGs, in which each heartbeat is represented by Gaussian-shaped P, Q, R, S, and T wave components. Using this simulator, we generate synthetic data for four abnormal electrocardiogram (ECG) classes: atrial fibrillation (AF), atrial flutter (AFLT), premature ventricular complex (PVC), and Wolff-Parkinson-White Syndrome (WPW). We evaluate the utility of this synthetic data by conducting abnormal ECG classification using ten different DNN architectures. Our results demonstrate that synthetic-to-real training improves classification performance for three of the four target abnormalities, with the largest architecture-averaged gain of

33.2\%

observed for AFLT. Further analysis reveals that the performance enhancement from synthetic data is more pronounced with smaller real-world datasets. These findings suggest that domain-knowledge-based synthetic ECGs can serve as a useful pre-training resource, particularly in scenarios where real-world data are limited or difficult to obtain.

Electrocardiogram Classification Pediatric-Adult Electrocardiogram Alignment Synthetic Data 3D Gaussian Splatting

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