1 citations · 1 across the 5 of their papers we have counts for
5 papers
Epistemic Uncertainty in Conformal Scores: A Unified Approach
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos +1
Conformal prediction methods create prediction bands with distribution-free guarantees but do not explicitly capture epistemic uncertainty, which can lead to overconfident predicti…
Conformal Calibration of Statistical Confidence Sets
Luben M. C. Cabezas, Guilherme P. Soares, Thiago R. Ramos +2
Constructing valid confidence sets is a crucial task in statistical inference, yet traditional methods often face challenges when dealing with complex models or limited observed sa…
Regression Trees for Fast and Adaptive Prediction Intervals
Luben M. C. Cabezas, Mateus P. Otto, Rafael Izbicki +1
Predictive models make mistakes. Hence, there is a need to quantify the uncertainty associated with their predictions. Conformal inference has emerged as a powerful tool to create…
REACT to NHST: Sensible conclusions to meaningful hypotheses
Rafael Izbicki, Luben M. C. Cabezas, Fernando A. B. Colugnatti +3
While Null Hypothesis Significance Testing (NHST) remains a widely used statistical tool, it suffers from several shortcomings in its common usage, such as conflating statistical a…
Hierarchical clustering: visualization, feature importance and model selection
Luben M. C. Cabezas, Rafael Izbicki, Rafael B. Stern
We propose methods for the analysis of hierarchical clustering that fully use the multi-resolution structure provided by a dendrogram. Specifically, we propose a loss for choosing…