collaborators

8 papers

stat.ML2026

CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference

Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos +2

Current experimental scientists have been increasingly relying on simulation-based inference (SBI) to invert complex non-linear models with intractable likelihoods. However, poster…

stat.ML2026

Conformal Prediction via Transported Beta Laws

Thiago R. Ramos, Helton Graziadei, Luben M. C. Cabezas

Split conformal prediction provides finite-sample marginal coverage under exchangeability, but this guarantee averages over the random calibration sample. We study instead the law…

stat.ML2026

LOCUS: A Distribution-Free Loss-Quantile Score for Risk-Aware Predictions

Matheus Barreto, Mário de Castro, Thiago R. Ramos +2

Modern machine learning models can be accurate on average yet still make mistakes that dominate deployment cost. We introduce Locus, a distribution-free wrapper that produces a per…

stat.ML2026

LoBoost: Fast Model-Native Local Conformal Prediction for Gradient-Boosted Trees

Vagner Santos, Victor Coscrato, Luben Cabezas +2

Gradient-boosted decision trees are among the strongest off-the-shelf predictors for tabular regression, but point predictions alone do not quantify uncertainty. Conformal predicti…

stat.ML2026

Conformal Prediction for Compositional Data

Lucas P. Amaral, Luben M. C. Cabezas, Thiago R. Ramos +1

Dirichlet regression models are suitable for compositional data, in which the response variable represents proportions that sum to one. However, there are still no well-established…

cs.DB2025

From Patents to Dataset: Scraping for Oxide Glass Compositions and Properties

Gustavo Laranja Thomaello, Thomaz Yeiden Busnardo Aguena, Eric Trevelato Costa +4

In this work, we present web scraping techniques to extract in- formation from patent tables, clean and structure them for future use in predictive machine learning models to devel…