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IEEE6mon
Variational Encoder Based Synthetic Alzheimer's Data Generation for Deep Learning, XGBoost and Statistical Survival Analysis
This study uses deep learning, specifically Variational Autoencoders (VAEs), to generate synthetic datasets that replicate real-world AD data while preserving privacy. These datasets were used to ...
GitHub8mon
GitHub - SeyedMuhammadHosseinMousavi/Synthetic-Data-Generation-Algorithms: Synthetic Data Generation Algorithms (VAE-GAN-Diffusion Model-LSTM-Copula)
Synthetic Data Generation Algorithms ... This repository demonstrates various synthetic data generation techniques using Variational Autoencoders (VAE), Generative Adversarial Networks ... 80% of the ...
Yahoo Finance1y
Global Synthetic Data Generation Markets Report 2023-2028: Analysis of Generative Adversarial Networks, Deep Reinforcement Learning from Human Feedback, & Variational Autoencoders
The global market for synthetic data generation was valued at $381.3 million in 2022. It is estimated that the revenue will grow to $2.1 billion during the forecast period of 2023 to 2028.
ascopubs.org1y
Synthetic Data Improve Survival Status Prediction Models in Early-Onset Colorectal Cancer | JCO Clinical Cancer Informatics - ASCO Publications
Training with the synthetic data and validating with the original data showed the highest performances of 0.850, 0.836, and 0.790 for the Decision Tree, Random Forest, and XGBoost models, respectively ...
Business Line1mon
Synthetic data fill AI training gaps, but can’t replace real-world nuance, experts say
Synthetic data fill AI training gaps, but can’t replace real-world nuance, experts say GenAI tools—especially models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs ...
Yahoo Finance2y
Global Synthetic Data Generation (Tabular, Text, Image, and Video) Industry Research Report 2023 - Yahoo Finance
The global synthetic data generation size is expected to grow from USD 300 million in 2023 to USD 2.1 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 45.7% ...
IEEE4mon
A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders - IEEE Xplore
Cyberattacks, especially data injection attacks, are becoming more common as smart grids are increasingly interconnected. In addition, accurate and unbiased high-quality data is required for model ...