Publications

L. M. C. Cabezas, V. S. Santos, T. R. Ramos, P. L. C. Rodrigues, Rafael Izbicki (2026). CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference. Philosophical Transactions of the Royal Society A.

James Carzon, Luca Masserano, Joshua D. Ingram, Alex Shen, Antonio Carlos Herling Ribeiro Junior, Tommaso Dorigo, Michele Doro, Joshua S. Speagle, Rafael Izbicki, Ann B. Lee (2026). Trustworthy Scientific Inference with Generative Models. Machine Learning: Science and Technology.

J. M. Stern, C. A. de B. Pereira, M. de Souza Lauretto, L. G. Esteves, Rafael Izbicki, R. B. Stern, M. A. Diniz, W. de Souza Borges (2026). The e-Value and the Full Bayesian Significance Test: Logical Properties and Philosophical Consequences. Walter Carnielli on Reasoning, Paraconsistency, and Probability, Outstanding Contributions to Logic, vol. 32.

M. B. Comito, Rafael Izbicki, P. do C. Hubert Junior, F. Moura (2026). Improving decision-making in construction: Nonparametric modeling of weather-induced impacts. Communications in Statistics: Case Studies, Data Analysis and Applications.

L. M. C. Cabezas, V. S. Santos, T. R. Ramos, Rafael Izbicki (2025). Epistemic Uncertainty in Conformal Scores: A Unified Approach. Proceedings of Machine Learning Research (UAI Track; Oral Presentation).

B. Dey, D. Zhao, B. Andrews, J. Newman, Rafael Izbicki, A. Lee (2025). Towards instance-wise calibration: Local amortized diagnostics and reshaping of conditional densities (LADaR). Machine Learning: Science and Technology.

Rafael Izbicki, L. M. C. Cabezas, F. A. B. Colugnatti, R. F. L. Lassance, A. A. L. de Souza, R. B. Stern (2025). REACT to NHST: Sensible conclusions for meaningful hypotheses. The Quantitative Methods for Psychology.

A. Fröhlich, T. Ramos, G. Cabello, I. Buzatto, Rafael Izbicki, D. Tiezzi (2025). PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification. In AAAI.

L. M. C. Cabezas, M. P. Otto, Rafael Izbicki, R. B. Stern (2025). Regression Trees for Fast and Adaptive Prediction Intervals . Information Sciences.

T. Dorigo, M. Aehle, C. Arcaro, M. Awais, F. Bergamaschi, J. Doniti, M. Doro, N. R. Gauger, Rafael Izbicki, J. Kieseler A. B. Lee, L. Masserano, F. Nardi, R. Rajesh, L. R. Vergara, A. Shen (2025). Toward the End-to-End Optimization of the SWGO Array Layout. Nuclear Physics B.

T. Dorigo, M. Doro, M. Aehle, M. Awais, N. R. Gauger, Rafael Izbicki, J. Kieseler A. B. Lee, L. Masserano, F. Nardi, A. Shen, L. R. Vergara (2025). On the utility function of experiments in fundamental science. Physics Open.

D. Valle, L. Haneda, Rafael Izbicki, R. Kamimura, B. Azevedo, S. Gomes, A. Sanchez, D. Almeida (2025). Nonparametric quantification of uncertainty in multistep upscaling approaches: a case study on estimating forest biomass in the Brazilian Amazon. Science Of Remote Sensing.

R. F. L. Lassance, Rafael Izbicki, R. B. Stern (2025). Adding Imprecision to Hypotheses: A Bayesian Framework for Testing Practical Significance in Nonparametric Settings. International Journal of Approximate Reasoning.

Y. Xiao, G. Soares, L. Bastos, Rafael Izbicki, P. Moraga (2025). Dengue nowcasting in Brazil by combining official surveillance data and Google Trends information. Plos One Neglected Tropical Diseases.

N. Dalmasso, L. Masserano, D. Zhao, Rafael Izbicki, A. B. Lee (2024). Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference. Electronic Journal of Statistics.

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L. Masserano, A. Shen, M. Doro, T. Dorigo, Rafael Izbicki, A. B. Lee (2024). Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference. Proceedings of Machine Learning Research (ICML Track).

V. Dheur, T. Bosser, Rafael Izbicki, S. Ben Taieb (2024). Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes. Machine Learning.

G. O. Assunção, Rafael Izbicki, M. O. Prates (2024). Is augmentation effective in improving prediction in imbalanced datasets?. Machine Learning.

J. F. A. Silva, Rafael Izbicki, L. S. Bastos, G. P. Soares (2024). Monitoring Viral Infections in Severe Acute Respiratory Syndrome Patients in Brazil. Developments in Statistical Modelling.

D. Valle, R. Leite, Rafael Izbicki, C. Silva, L. Haneda (2024). Local uncertainty maps for land-use/land-cover classification without remote sensing and modeling work using a class-conditional conformal approach . International Journal of Applied Earth Observation and Geoinformation.

G. Grivol, Rafael Izbicki, A. A. Okuno, R. B. Stern (2024). Flexible conditional density estimation for time series. Brazilian Journal of Probability and Statistics.

L. Nakazono, R. R. Valença, G. Soares, Rafael Izbicki, Ž. Ivezić (2024). The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts. Monthly Notices of the Royal Astronomical Society.

T. McNeely, G. Vincente, K. M. Wood, Rafael Izbicki, A. B. Lee (2023). Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery. Annals of Applied Statistics (Selected for The Best of AOAS invited paper session at JSM 2023).

A. Shen, L. Masserano, Rafael Izbicki, T. Dorigo, M. Doro, A. B. Lee (2023). Classification under Prior Probability Shift in Simulator-Based Inference: Application to Atmospheric Cosmic-Ray Showers. NeurIPS (Machine Learning and the Physical Sciences Workshop; Best Poster Award).

F. M. Polo, Rafael Izbicki, E. G. Lacerda Jr, J. P. Ibieta-Jimenez, R. Vicente (2023). A unified framework for dataset shift diagnostics. Information Sciences.

L. Masserano, T. Dorigo, Rafael Izbicki, M. Kuusela, A. B. Lee (2023). Simulation-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems. Proceedings of Machine Learning Research (AISTATS track; Finalist at the ASA SPES and Q&P Student Paper Competition).

L. M. C. Cabezas, Rafael Izbicki, R. B. Stern (2023). Hierarchical clustering: visualization, feature importance and model selection. Applied Soft Computing Journal.

D. Valle, Rafael Izbicki, R. Leite (2023). Quantifying uncertainty in land-use land-cover classification using conformal statistics. Remote Sensing of Environment.

V. Coscrato, M. H. A. Inacio, T. Botari, Rafael Izbicki (2023). NLS: An accurate and yet easy-to-interpret prediction method . Neural Networks.

Luís G. Esteves, Rafael Izbicki, Julio M. Stern, Rafael B. Stern (2023). Logical coherence in Bayesian simultaneous three-way hypothesis tests. In International Journal of Approximate Reasoning.

G. Shimizu, Rafael Izbicki, D. Valle (2023). A new LDA formulation with covariates. Communications in Statistics - Simulation and Computation.

Rafael Izbicki, Gilson Shimizu, Rafael B. Stern (2022). CD-split and HPD-split: Efficient conformal regions in high dimensions. Journal of Machine Learning Research.

N. Dalmasso, L. Masserano, D. Zhao, Rafael Izbicki, A. B. Lee (2022). Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage. Submitted.

M. H. de A. Inácio, Rafael Izbicki, D. L. Lopes, M. A. Diniz, L. E. B. Salasar, J. Poloniato (2022). What if the forecaster knew? Assessing forecast reliability via simulation. TEMA..

S. G. Feronato, M. L. M. Silva, Rafael Izbicki, T. D. J. Farias, P. Shigunov, B. Dallagiovanna, F. Passetti, H. G. dos Santos (2022). Selecting Genetic Variants and Interactions Associated with Amyotrophic Lateral Sclerosis: A Group LASSO Approach. Journal Of Personalized Medicine.

D. Zhao, N. Dalmasso, Rafael Izbicki, A. B. Lee (2021). Diagnostics for Conditional Density Models and Bayesian Inference Algorithms. Proceedings of Machine Learning Research (UAI Track).

Mateus B. Comito, Rafael Izbicki, Rafael B. Stern, Julio A. Z. Trecenti (2021). Causas de desaparecimento no estado de São Paulo entre 2013 e 2014: uma análise automatizada de boletins de ocorrência. In RDPESP.

T. McNeely, G. Vincent, Rafael Izbicki, K. M. Wood, A. B. Lee (2021). Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones. Tackling Climate Change with Machine Learning workshop at NeurIPS 2021 (poster).

D. Valle, G. Shimizu, Rafael Izbicki, L. Maracahipes, D. Silvério, L. Paolucci, Y. Jameel, P. Brando (2021). The Latent Dirichlet Allocation model with covariates (LDAcov): a case study on the effect of fire on species composition in Amazonian forests. Ecology and Evolution.

M. H. de A. Inácio, Rafael Izbicki, B. Gyires-Tóth (2021). Distance assessment and analysis of high-dimensional samples using variational autoencoders. Information Sciences.

Rafael Izbicki, L. S. Bastos, M. Izbicki, H. F. Lopes, T. M. dos Santos (2021). How many hospitalizations has the COVID-19 vaccination already prevented in São Paulo?. Clinics.

Rafael Izbicki, M. A. Diniz, L. S Bastos (2020). Sensitivity and specificity in prevalence studies: the importance of considering uncertainty. Clinics.

Victor Coscrato, Rafael Izbicki, Rafael B. Stern (2020). Agnostic tests can control the type I and type II errors simultaneously. In BJPS.

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Gilson Shimizu, Rafael Izbicki, Rafael B. Stern (2020). Flexible distribution-free conditional predictive bands using density estimators. In PMLR.

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Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee (2020). Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. Proceedings of Machine Learning Research (ICML Track).

N. Dalmasso, A. B. Lee, Rafael Izbicki, T. Pospisil, I. Kim, C. Lin (2020). Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations. Proceedings of Machine Learning Research (AISTATS Track).

V. A. Coscrato, M. H. de A. Inácio, Rafael Izbicki (2020). The NN-Stacking: Feature weighted linear stacking through neural networks. Neurocomputing.

N. Dalmasso, T. Pospisil, A. B. Lee, Rafael Izbicki, P. E. Freeman, A. I. Malz (2020). Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference. Astronomy and Computing.

R. de C. Ceregatti, Rafael Izbicki, L. E. B. Salasar (2020). WIKS: A general Bayesian nonparametric index for quantifying differences between two populations. Test.

S. Schmidt, A. Malz, et al., Rafael Izbicki (2020). Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST). Monthly Notices of the Royal Astronomical Society.

L. M. Borges, V. C. Reis, Rafael Izbicki (2020). Schrödinger's phenotypes: herbarium specimens show two-dimensional images are both good and (not so) bad sources of morphological data. Methods in Ecology and Evolution.

T. Botari, Rafael Izbicki, A. C. P. L. F. Carvalho (2020). Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space. Communications in Computer and Information Science.

M. Musetti, Rafael Izbicki (2020). Combinando métodos de aprendizado supervisionado para a melhoria da previsão do redshift de galáxia. TEMA – Tendências em Matemática Aplicada e Computacional.

Luís G. Esteves, Rafael Izbicki, Julio M. Stern, Rafael B. Stern (2019). Pragmatic hypotheses in the evolution of Science. In Entropy.

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Afonso F. Vaz, Rafael Izbicki, Rafael B. Stern (2019). Quantification under prior probability shift: the ratio estimator and its extensions. Journal of Machine Learning Research.

Rafael Izbicki, Taylor Pospisil, Ann B. Lee (2019). ABC-CDE: Toward Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations. Journal of Computational and Graphical Statistics.

H. G. dos Santos, C. F. do Nascimento, Rafael Izbicki, Y. A. de O. Duarte, A. D. P. Chiavegatto Filho (2019). Machine learning para análises preditivas em saúde: exemplo de aplicação para predizer óbito em idosos de São Paulo. Caderno de Saúde Pública.

Couto, Cumming, Congrains, Rafael Izbicki, Braga, Rocha, Moralez-Silva, Henry, Manu, Abalaka, Regalla, Silva, Diop, Lama (2019). Avian haemosporidians in the cattle egret (Bubulcus ibis) from central-western and southern Africa: high diversity and prevalence. PLOS ONE.

M. A. Diniz, Rafael Izbicki, D. L. Lopes, L. E. B. Salasar (2019). Comparing probabilistic predictive models applied to football. Journal of the Operational Research Society..

M. H. de A. Inácio, Rafael Izbicki, L. E. B. Salasar (2018). Comparing two populations using Bayesian Fourier series density estimation. Communications in Statistics – Simulation and Computation..

M. H. de A. Inácio, Rafael Izbicki (2018). Conditional density estimation using Fourier series and neural networks. KDMiLe - Symposium on Knowledge Discovery, Mining and Learning - Algorithms Track.

F. M. da Silva, C. I. Niño, Rafael Izbicki, S. N. del. Lama" (2018). Considerations for monitoring population trends of colonial waterbirds using the effective number of breeders and census estimates . Ecology and Evolution..

Luís G. Esteves, Rafael Izbicki, Rafael B. Stern (2018). Teaching Decision Theory proof strategies using a crowdsourcing problem. In TAS.

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L. O. Cruz, Rafael Izbicki (2018). Monitoramento online da dengue: usando o Google para predizer epidemias.. Revista Brasileira de Biometria.

I. Aprahamian, E. Sassaki, M. Santos, Rafael Izbicki, R. C. Pulgrossi, M. Biella, A. C. Borges, M. Sassaki, L. Torres, I. Fernandez, O. Piao, P. Castro, P. Piao, M. S. Yassuda (2018). Hypertension is associated with frailty in older adults. The Journal of Clinical Hypertension..

Rafael Izbicki, Ann B. Lee (2017). Converting High-Dimensional Regression to High-Dimensional Conditional Density Estimation. Electronic Journal of Statistics.

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P.E. Freeman, Rafael Izbicki, A.B. Lee (2017). A unified framework for constructing, tuning and assessing photometric redshift density estimates in a selection bias setting. Monthly Notices of the Royal Astronomical Society.

V. Fossaluza, Rafael Izbicki, G. M. Silva, L. G. Esteves (2017). Coherent hypothesis testing. The American Statistician.

Julio M. Stern, Rafael Izbicki, Luís G. Esteves, Rafael B. Stern (2017). Logically-consistent hypothesis testing and the hexagon of oppositions. In LJIGPL.

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Afonso F. Vaz, Rafael Izbicki, Rafael B. Stern (2017). Prior Shift Using the Ratio Estimator. In 37th MaxEnt.

Rafael Izbicki, Ann B. Lee, Peter E. Freeman (2017). Photo-z estimation: An example of nonparametric conditional density estimation under selection bias. The Annals of Applied Statistics.

N.O.C. Cezar, Rafael Izbicki, D. Cardoso, G.C. Almeida, L. Valiengo, M.V.Z. Camargo, V.F. Orestes, I. Aprahamian, M. S. Yassuda (2017). Frailty in older adults with aMCI due to AD: a comparison of two models of frailty characterization. Geriatrics & Gerontology International.

I. Aprahamian, N.O.C. Cezar, Rafael Izbicki, S.M. Lin, D.L.V. Paulo, A. Fattori, M. M. Biella, W. Jacob Filho, M.S. Yassuda (2017). Screening for frailty with the FRAIL scale: a comparison with the phenotype criteria. Journal of the American Medical Directors Association..

P. Ianishi, Rafael Izbicki (2017). Classificação morfológica de galáxias em conjuntos de dados desbalanceados.. TEMA – Tendências em Matemática Aplicada e Computacional.

Rafael Izbicki, A. B. Lee (2016). Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting.. Journal of Computational and Graphical Statistics.

A. B. Lee, Rafael Izbicki (2016). A Spectral Series Approach to High-Dimensional Nonparametric Regression.. Electronic Journal of Statistics.

Luís G. Esteves, Rafael Izbicki, Julio M. Stern, Rafael B. Stern (2016). The Logical Consistency of Simultaneous Agnostic Hypothesis Tests. In Entropy.

L. G. Esteves, Rafael Izbicki, J. M. Stern, R. B. Stern (2016). The Logical Consistency of Simultaneous Agnostic Hypothesis Tests. Entropy.

G. M. Silva, L. G. Esteves, V. Fossaluza, Rafael Izbicki, S. Wechsler (2016). A Bayesian Decision-Theoretic Approach to Logically-Consistent Hypothesis Testing. Entropy.

J. F. Cecato, J. E. Martinelli, Rafael Izbicki, M. S. Yassuda, I. Aprahamian (2016). A subtest analysis of the Montreal cognitive assessment (MoCA): which subtests can best discriminate between healthy controls, mild cognitive impairment and Alzheimer’s disease?. International Psychogeriatrics.

Rafael Izbicki, L. G. Esteves (2015). Logical consistency in simultaneous statistical test procedures. Logic Journal of the IGPL.

Rafael Izbicki, A. B. Lee, C. M. Schafer (2014). High-Dimensional density ratio estimation with extensions to approximate likelihood computation. Journal of Machine Learning Research (AISTATS Track).

P. E. Freeman, Rafael Izbicki, A. B. Lee, J.A. Newman, C. J. Conselice, A.M. Koekemoer, J.M. Lotz, M. Mozena (2013). New image statistics for detecting disturbed galaxy morphologies at high redshift. Statistical Analysis and Data Mining.

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F. C. Gomes, A. G. Andrade, Rafael Izbicki, A. Moreira-Almeida, L. G. Oliveira (2013). Religion as a protective factor against drug use among Brazilian university students: a national survey. Revista Brasileira de Psiquiatria.

S. Wechsler, Rafael Izbicki, L. G. Esteves (2013). A Bayesian Look at Nonidentifiability: a Simple Example. The American Statistician.

Rafael Izbicki, Rafael B. Stern (2013). Learning with many experts: Model selection and sparsity. In SAM.

Rafael Izbicki, V. Fossaluza, A. G. Hounie, E. Y. Nakano, C. A. de B. Pereira (2012). Testing Allele Homogeneity: The Problem of Nested Hypotheses. BMC Genetics.

H. Brentani, E. Y. Nakano, C. B. Martins, Rafael Izbicki, C. A. de B. Pereira (2011). Disequilibrium Coefficient: A Bayesian Perspective. Statistical Applications in Genetics and Molecular Biology.

R. Barcelos-Ferreira, Rafael Izbicki, D. C. Steffens, C. M. C. Bottino (2010). Depressive morbidity and gender in community-dwelling Brazilian elderly: systematic review and meta-analysis. International Psychogeriatrics.

I. Aprahamian, B. S. Diniz, Rafael Izbicki, M. Radanovic, P. V. Nunes, O. V. Forlenza (2010). Optimizing the CAMCOG test in the screening for mild cognitive impairment and incipient dementia: saving time with relevant domains. International Journal of Geriatric Psychiatry.

I. Aprahamian, J. E. Martinelli, J. Cecato, Rafael Izbicki, M. S. Yassuda (2010). Can the CAMCOG be a good cognitive test for patients with Alzheimer’s disease with low levels of education?. International Psychogeriatrics.