24 citations · 30 across the 10 of their papers we have counts for
3 papers · 1 filter
Artificial Inductive Bias for Synthetic Tabular Data Generation in Data-Scarce Scenarios
Patricia A. Apellániz, Ana Jiménez, Borja Arroyo Galende +2
While synthetic tabular data generation using Deep Generative Models (DGMs) offers a compelling solution to data scarcity and privacy concerns, their effectiveness relies on the av…
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…
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…