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Rafael Izbicki

Has grant

Assistant Professor

Universidade Federal de São Carlos

Brazil

Research Interests

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Professors in Biostatistics

Recent Grants

Grant: Close

Predição de redshifts fotométricos: utilizando erros de medida

Open Date: 2024-05-01

Close Date: 2025-04-30

Grant: Close

Aprendizado estatístico de máquina: em direção a uma melhor quantificação de incerteza

Open Date: 2023-10-01

Close Date: 2025-09-30

Grant: Open

Validation and calibration of prediction models

Open Date: 2022-10-01

Close Date: 2027-09-30

Grant: Close

Aprendizado estatístico de máquina - em direção a uma melhor quantificação de incerteza

Open Date: 2022-01-01

Close Date:

Grant: Close

Seleção de Variáveis Escalável para Métodos baseados em Espaços de Hilbert de reprodução

Open Date: 2021-10-01

Close Date: 2023-03-31

Articles (20)

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2024

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2024

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2024

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Istituto Nazionale di Fisica Nucleare

ITALY

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Rafael Izbicki

Research Interests

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Recent Grants

Articles (20)

Trustworthy scientific inference with generative models

On focusing statistical power for searches and measurements in particle physics

Model interpretation using improved local regression with variable importance

Tabular Foundation Models for the Estimation of Probabilistic Quasar Photometric Redshifts in S-PLUS

CP4SBI: local conformal calibration of credible sets in simulation-based inference

Is Augmentation Effective in Improving Prediction in Imbalanced Datasets?

Toward the end-to-end optimization of the SWGO array layout

Regression trees for fast and adaptive prediction intervals

Towards instance-wise calibration: local amortized diagnostics and reshaping of conditional densities (LADaR)

Nonparametric quantification of uncertainty in multistep upscaling approaches: A case study on estimating forest biomass in the Brazilian Amazon

Adding imprecision to hypotheses: A Bayesian framework for testing practical significance in nonparametric settings

Expertise-based weighting for regression models with noisy labels

On the utility function of experiments in fundamental science

PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification

The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts

Distribution-free conformal joint prediction regions for neural marked temporal point processes

Flexible conditional density estimation for time series

Likelihood-free frequentist inference: bridging classical statistics and machine learning for reliable simulator-based inference

Local uncertainty maps for land-use/land-cover classification without remote sensing and modeling work using a class-conditional conformal approach

A new LDA formulation with covariates

Collaborators (10)

Joshua Shen Speagle

Rafael Stern

Nina Hirata

Ann Lee

Andre de Carvalho

Brett Andrews

Michele Doro

Denis Valle

Zeljko Ivezic

Cornelia Hanna Esther Arcaro

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