3 papers
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…
q-bio.PE2025
Approximate Bayesian Computation Made Easy: A Practical Guide to ABC-SMC for Dynamical Systems with \texttt{pymc}
Mario Castro
Mechanistic models are essential tools across ecology, epidemiology, and the life sciences, but parameter inference remains challenging when likelihood functions are intractable. A…
stat.ML2025
Effects of label noise on the classification of outlier observations
Matheus VinÃcius Barreto de Farias, Mario de Castro
This study investigates the impact of adding noise to the training set classes in classification tasks using the BCOPS algorithm (Balanced and Conformal Optimized Prediction Sets),…