Latest Articles for Synthetic Data

A method for better code generation in data science using input-output specifications.

Enhancing event identification through semi-supervised learning and synthetic data generation.

Explore how dataset choices affect machine learning models predicting antibody binding.

A new method for predicting causal relationships from time series data using deep learning.

A new method for accurate 3D movement tracking using video data.

New methods improve protein folding studies with synthetic data generation.

MOVE integrates biological data to enhance cancer research and treatment strategies.

This article explores a method to stabilize generative models using synthetic data.

A look at RAG and fine-tuning methods for enhancing LLMs' performance on rare topics.

Exploring the effectiveness of real vs. synthetic data in time series models.

cDVGAN improves synthetic data for gravitational waves and glitches, aiding detection methods.

Exploring how large language models can improve model generalization.

A new mechanism enhances synthetic data generation while protecting individual privacy.

Introducing a new approach to generate effective datasets using synthetic data.

This study enhances facial AU detection using synthetic data for better accuracy and fairness.

Researchers are using synthetic data to improve human pose estimation.

This article presents a new method for improving visual grounding by merging data and model knowledge.

DepthFM improves speed and accuracy in depth estimation using flow matching techniques.

Research explores using translationese to enhance performance of language models for low-resource languages.

Research shows synthetic data can aid deep learning in forestry tasks.

ARSim method improves data quality for training self-driving cars using synthetic objects.

A new method enhances assembly accuracy and efficiency in medical and industrial settings.

A method to enhance how machines interpret complex chart questions.

A method for generating synthetic data using Bayesian networks to protect privacy while allowing analysis.

scGFT offers a solution for creating synthetic single-cell RNA data efficiently.

Synthetic data is reshaping surgical planning and training in neurosurgery.

Synthetic data offers promise for improving research on adolescent cancer patients.

Diff-Mix improves image classification by creating diverse synthetic data.

Gecko offers an efficient model for processing and comparing texts effectively.

Exploring the role of Bayesian Neural Networks in turbulent flow prediction.

This study analyzes the effectiveness of synthetic images in face recognition systems.

Synthetic data enables companies to share insights while protecting sensitive information.

New methods enhance patient privacy while improving medical image research.

New techniques improve heart disease predictions and personalized treatment options.

A structured framework for assessing synthetic data generation methods.

Examining how LLMs can perform regression without additional training.

Researchers aim to generate balanced synthetic data to prevent bias in machine learning.

Exploring key factors affecting robustness against adversarial attacks in machine learning.

DataTune improves synthetic dataset generation for better language model training.

A new dataset enhances detection of unusual events in industrial settings.