3 papers
cs.LG2026
Beyond the Mean: Distribution-Aware Loss Functions for Bimodal Regression
Abolfazl Mohammadi-Seif, Carlos Soares, Rita P. Ribeiro +1
Despite the strong predictive performance achieved by machine learning models across many application domains, assessing their trustworthiness through reliable estimates of predict…
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.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…