4 citations · 4 across the 5 of their papers we have counts for
5 papers
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…
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…
Effects of label noise on the classification of outlier observations
Matheus Vinícius 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),…
A new regression model for positive data
Marcelo Bourguignon, Manoel Santos-Neto, Mário de Castro
In this paper, we propose a regression model where the response variable is beta prime distributed using a new parameterization of this distribution that is indexed by mean and pre…
A Poisson Mixed Model with Nonnormal Random Effect Distribution
Lizandra C. Fabio, Gilberto A. Paula, Mario de Castro
We propose in this paper a random intercept Poisson model in which the random effect distribution is assumed to follow a generalized log-gamma (GLG) distribution. We derive the fir…