3 papers
cs.LG2026
Exploring Transformer Placement in Variational Autoencoders for Tabular Data Generation
Aníbal Silva, Moisés Santos, André Restivo +1
Tabular data remains a challenging domain for generative models. In particular, the standard Variational Autoencoder (VAE) architecture, typically composed of multilayer perceptron…
cs.LG2026
Grasynda: Graph-based Synthetic Time Series Generation
Luis Amorim, Moises Santos, Paulo J. Azevedo +2
Data augmentation is a crucial tool in time series forecasting, especially for deep learning architectures that require a large training sample size to generalize effectively. Howe…
cs.LG2024
Tabular data generation with tensor contraction layers and transformers
Aníbal Silva, André Restivo, Moisés Santos +1
Generative modeling for tabular data has recently gained significant attention in the Deep Learning domain. Its objective is to estimate the underlying distribution of the data. Ho…