Bayesian Statistics

Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
The paper introduces a novel approach to classifying events under generalized label shift by framing classification as hypothesis testing, which leads to valid uncertainty quantification. This is demonstrated through applications in biology and astroparticle physics.
L. Masserano, A. Shen, M. Doro, T. Dorigo, Rafael Izbicki, A. B. Lee
May, 2024 Proceedings of Machine Learning Research (ICML Track)
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Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
Simulation-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems
L. Masserano, T. Dorigo, Rafael Izbicki, M. Kuusela, A. B. Lee
February, 2023 Proceedings of Machine Learning Research (AISTATS track)
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What if the forecaster knew? Assessing forecast reliability via simulation
M. H. de A. Inácio, Rafael Izbicki, D. L. Lopes, M. A. Diniz, L. E. B. Salasar, J. Poloniato
January, 2022 TEMA.
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Comparing probabilistic predictive models applied to football
We propose two Bayesian multinomial-Dirichlet models to predict the final outcome of football (soccer) matches and compare them to …
M. A. Diniz, Rafael Izbicki, D. L. Lopes, L. E. B. Salasar
January, 2019 Journal of the Operational Research Society.
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A Bayesian Look at Nonidentifiability: a Simple Example
This article discusses the concept of identifiability in simple probability calculus. Emphasis is given to Bayesian solutions. In …
S. Wechsler, Rafael Izbicki, L. G. Esteves
November, 2013 The American Statistician
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Testing Allele Homogeneity: The Problem of Nested Hypotheses
Rafael Izbicki, V. Fossaluza, A. G. Hounie, E. Y. Nakano, C. A. de B. Pereira
November, 2012 BMC Genetics paper
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