3 papers
cs.LG2024
Synthetic Tabular Data Validation: A Divergence-Based Approach
Patricia A. Apellániz, Ana Jiménez, Borja Arroyo Galende +2
The ever-increasing use of generative models in various fields where tabular data is used highlights the need for robust and standardized validation metrics to assess the similarit…
cs.LG2024
An improved tabular data generator with VAE-GMM integration
Patricia A. Apellániz, Juan Parras, Santiago Zazo
The rising use of machine learning in various fields requires robust methods to create synthetic tabular data. Data should preserve key characteristics while addressing data scarci…
cs.LG2023
SAVAE: Leveraging the variational Bayes autoencoder for survival analysis
Patricia A. Apellániz, Juan Parras, Santiago Zazo
As in many fields of medical research, survival analysis has witnessed a growing interest in the application of deep learning techniques to model complex, high-dimensional, heterog…