Rafael Izbicki

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 48

Top Topics

Density Estimation

Hypothesis Test

Bayesian Decision

High Dimensions

Top Venues

Publications

Luca Masserano, Alex Shen, Michele Doro, Tommaso Dorigo, Rafael Izbicki, Ann B. Lee
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference. CoRR (2024)
Victor Dheur, Tanguy Bosser, Rafael Izbicki, Souhaib Ben Taieb
Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes. CoRR (2024)
Luben M. C. Cabezas, Mateus P. Otto, Rafael Izbicki, Rafael Bassi Stern
Regression Trees for Fast and Adaptive Prediction Intervals. CoRR (2024)
Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee
Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems. AISTATS (2023)
Victor Coscrato, Marco Henrique de Almeida Inácio, Tiago Botari, Rafael Izbicki
NLS: An accurate and yet easy-to-interpret prediction method. Neural Networks 162 (2023)
Felipe Maia Polo, Rafael Izbicki, Evanildo G. Lacerda Jr., Juan Pablo Ibieta-Jimenez, Renato Vicente
A unified framework for dataset shift diagnostics. Inf. Sci. 649 (2023)
Luís Gustavo Esteves, Rafael Izbicki, Julio Michael Stern, Rafael Bassi Stern
Logical coherence in Bayesian simultaneous three-way hypothesis tests. Int. J. Approx. Reason. 152 (2023)
Gabriel O. Assunção, Rafael Izbicki, Marcos O. Prates
Is augmentation effective to improve prediction in imbalanced text datasets? CoRR (2023)
Gustavo Grivol, Rafael Izbicki, Alex A. Okuno, Rafael Bassi Stern
Flexible conditional density estimation for time series. CoRR (2023)
Milene Regina dos Santos, Rafael Izbicki
Expertise-based Weighting for Regression Models with Noisy Labels. CoRR (2023)
Luben M. C. Cabezas, Rafael Izbicki, Rafael Bassi Stern
Hierarchical clustering: Visualization, feature importance and model selection. Appl. Soft Comput. 141 (2023)
Gilson T. Shimizu, Rafael Izbicki, Denis Valle
A new LDA formulation with covariates. CoRR (2022)
Biprateep Dey, David Zhao, Jeffrey A. Newman, Brett H. Andrews, Rafael Izbicki, Ann B. Lee
Calibrated Predictive Distributions via Diagnostics for Conditional Coverage. CoRR (2022)
Gilson Y. Shimizu, Rafael Izbicki, Andre C. P. L. F. de Carvalho
Model interpretation using improved local regression with variable importance. CoRR (2022)
Rafael Izbicki, Gilson Y. Shimizu, Rafael Bassi Stern
CD-split and HPD-split: Efficient Conformal Regions in High Dimensions. J. Mach. Learn. Res. 23 (2022)
Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee
Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm. CoRR (2022)
Mateus P. Otto, Rafael Izbicki
RFFNet: Scalable and interpretable kernel methods via Random Fourier Features. CoRR (2022)
Felipe Maia Polo, Rafael Izbicki, Evanildo Gomes Lacerda Jr., Juan Pablo Ibieta-Jimenez, Renato Vicente
A unified framework for dataset shift diagnostics. CoRR (2022)
Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
Distance assessment and analysis of high-dimensional samples using variational autoencoders. Inf. Sci. 557 (2021)
Niccolò Dalmasso, David Zhao, Rafael Izbicki, Ann B. Lee
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification. CoRR (2021)
Trey McNeely, Galen Vincent, Rafael Izbicki, Kimberly M. Wood, Ann B. Lee
Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones. CoRR (2021)
David Zhao, Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
Diagnostics for conditional density models and Bayesian inference algorithms. UAI (2021)
Biprateep Dey, Jeffrey A. Newman, Brett H. Andrews, Rafael Izbicki, Ann B. Lee, David Zhao, Markus Michael Rau, Alex I. Malz
Re-calibrating Photometric Redshift Probability Distributions Using Feature-space Regression. CoRR (2021)
Luben M. C. Cabezas, Rafael Izbicki, Rafael Bassi Stern
Hierarchical clustering: visualization, feature importance and model selection. CoRR (2021)
Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. CoRR (2020)
Tiago Botari, Frederik Hvilshøj, Rafael Izbicki, André C. P. L. F. de Carvalho
MeLIME: Meaningful Local Explanation for Machine Learning Models. CoRR (2020)
Marco Henrique de Almeida Inácio, Rafael Izbicki, Luis Ernesto Salasar
Comparing two populations using Bayesian Fourier series density estimation. Commun. Stat. Simul. Comput. 49 (1) (2020)
Rafael Izbicki, Gilson T. Shimizu, Rafael Bassi Stern
Flexible distribution-free conditional predictive bands using density estimators. AISTATS (2020)
Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee, Rafael Izbicki, Peter E. Freeman, Alex I. Malz
Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference. Astron. Comput. 30 (2020)
Victor Coscrato, Marco Henrique de Almeida Inácio, Rafael Izbicki
The NN-Stacking: Feature weighted linear stacking through neural networks. Neurocomputing 399 (2020)
Niccolò Dalmasso, Ann B. Lee, Rafael Izbicki, Taylor Pospisil, Ilmun Kim, Chieh-An Lin
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations. AISTATS (2020)
Rafael Izbicki, Gilson T. Shimizu, Rafael Bassi Stern
CD-split: efficient conformal regions in high dimensions. CoRR (2020)
Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting. ICML (2020)
Victor Coscrato, Marco Henrique de Almeida Inácio, Rafael Izbicki
The NN-Stacking: Feature weighted linear stacking through neural networks. CoRR (2019)
Rafael Izbicki, Gilson T. Shimizu, Rafael Bassi Stern
Distribution-free conditional predictive bands using density estimators. CoRR (2019)
Marco Henrique de Almeida Inácio, Rafael Izbicki, Rafael Bassi Stern
Conditional independence testing: a predictive perspective. CoRR (2019)
Tiago Botari, Rafael Izbicki, André C. P. L. F. de Carvalho
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space. PKDD/ECML Workshops (1) (2019)
Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders. CoRR (2019)
Victor Coscrato, Marco Henrique de Almeida Inácio, Tiago Botari, Rafael Izbicki
NLS: an accurate and yet easy-to-interpret regression method. CoRR (2019)
Luís Gustavo Esteves, Rafael Izbicki, Julio Michael Stern, Rafael Bassi Stern
Pragmatic Hypotheses in the Evolution of Science. Entropy 21 (9) (2019)
Márcio Alves Diniz, Rafael Izbicki, Danilo Lopes, Luis Ernesto Salasar
Comparing probabilistic predictive models applied to football. J. Oper. Res. Soc. 70 (5) (2019)
Tiago Botari, Rafael Izbicki, André C. P. L. F. de Carvalho
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space. CoRR (2019)
Afonso Fernandes Vaz, Rafael Izbicki, Rafael Bassi Stern
Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions. J. Mach. Learn. Res. 20 (2019)
Afonso Fernandes Vaz, Rafael Izbicki, Rafael Bassi Stern
Quantification under prior probability shift: the ratio estimator and its extensions. CoRR (2018)
Julio Michael Stern, Rafael Izbicki, Luís Gustavo Esteves, Rafael Bassi Stern
Logically-consistent hypothesis testing and the hexagon of oppositions. Log. J. IGPL 25 (5) (2017)
Luís Gustavo Esteves, Rafael Izbicki, Julio Michael Stern, Rafael Bassi Stern
The Logical Consistency of Simultaneous Agnostic Hypothesis Tests. Entropy 18 (7) (2016)
Rafael Izbicki, Luís Gustavo Esteves
Logical consistency in simultaneous statistical test procedures. Log. J. IGPL 23 (5) (2015)
Gustavo Miranda da Silva, Luís Gustavo Esteves, Victor Fossaluza, Rafael Izbicki, Sergio Wechsler
A Bayesian Decision-Theoretic Approach to Logically-Consistent Hypothesis Testing. Entropy 17 (10) (2015)
Rafael Izbicki, Ann B. Lee, Chad Schafer
High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation. AISTATS (2014)
Rafael Izbicki, Rafael Bassi Stern
Learning with many experts: model selection and sparsity. CoRR (2014)
Rafael Izbicki, Rafael Bassi Stern
Learning with many experts: Model selection and sparsity. Stat. Anal. Data Min. 6 (6) (2013)