24 citations · 67 across the 9 of their papers we have counts for
23 papers
Model interpretation using improved local regression with variable importance
Gilson Y. Shimizu, Rafael Izbicki, Andre C. P. L. F. de Carvalho
A fundamental question on the use of ML models concerns the explanation of their predictions for increasing transparency in decision-making. Although several interpretability metho…
Logical coherence in Bayesian simultaneous three-way hypothesis tests
Bernardo F. Reimann, Rafael Izbicki, Julio M. Stern +2
This paper studies whether Bayesian simultaneous three-way hypothesis tests can be logically coherent. Two types of results are obtained. First, under the standard error-wise const…
A new LDA formulation with covariates
Gilson Shimizu, Rafael Izbicki, Denis Valle
The Latent Dirichlet Allocation (LDA) model is a popular method for creating mixed-membership clusters. Despite having been originally developed for text analysis, LDA has been use…
Diagnostics for Conditional Density Models and Bayesian Inference Algorithms
David Zhao, Niccolò Dalmasso, Rafael Izbicki +1
There has been growing interest in the AI community for precise uncertainty quantification. Conditional density models f(y|x), where x represents potentially high-dimensional featu…
MeLIME: Meaningful Local Explanation for Machine Learning Models
Tiago Botari, Frederik Hvilshøj, Rafael Izbicki +1
Most state-of-the-art machine learning algorithms induce black-box models, preventing their application in many sensitive domains. Hence, many methodologies for explaining machine…
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
Parameter estimation, statistical tests and confidence sets are the cornerstones of classical statistics that allow scientists to make inferences about the underlying process that…