Rafael Izbicki

Juan Pablo Ibieta-Jimenez

Evanildo G. Lacerda Jr.

Renato Vicente

Inf. Sci., November, 2023

Hierarchical clustering: Visualization, feature importance and model selection.

[BibT_eX]

[DOI]

Luben M. C. Cabezas

Appl. Soft Comput., July, 2023

NLS: An accurate and yet easy-to-interpret prediction method.

[BibT_eX]

[DOI]

Victor Coscrato

Neural Networks, May, 2023

Logical coherence in Bayesian simultaneous three-way hypothesis tests.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2023

Expertise-based Weighting for Regression Models with Noisy Labels.

[BibT_eX]

[DOI]

Milene Regina dos Santos

CoRR, 2023

Is augmentation effective to improve prediction in imbalanced text datasets?

[BibT_eX]

[DOI]

Gabriel O. Assunção

Marcos O. Prates

CoRR, 2023

Flexible conditional density estimation for time series.

[BibT_eX]

[DOI]

CoRR, 2023

Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

CD-split and HPD-split: Efficient Conformal Regions in High Dimensions.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

RFFNet: Scalable and interpretable kernel methods via Random Fourier Features.

[BibT_eX]

[DOI]

Mateus P. Otto

CoRR, 2022

Model interpretation using improved local regression with variable importance.

[BibT_eX]

[DOI]

André C. P. L. F. de Carvalho

CoRR, 2022

Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm.

[BibT_eX]

[DOI]

CoRR, 2022

Calibrated Predictive Distributions via Diagnostics for Conditional Coverage.

[BibT_eX]

[DOI]

CoRR, 2022

A new LDA formulation with covariates.

[BibT_eX]

[DOI]

Denis Valle

CoRR, 2022

2021

Distance assessment and analysis of high-dimensional samples using variational autoencoders.

[BibT_eX]

[DOI]

Bálint Gyires-Tóth

Inf. Sci., 2021

Re-calibrating Photometric Redshift Probability Distributions Using Feature-space Regression.

[BibT_eX]

[DOI]

CoRR, 2021

Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones.

[BibT_eX]

[DOI]

CoRR, 2021

Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning in Simulation and Uncertainty Quantification.

[BibT_eX]

[DOI]

CoRR, 2021

Diagnostics for conditional density models and Bayesian inference algorithms.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

The NN-Stacking: Feature weighted linear stacking through neural networks.

[BibT_eX]

[DOI]

Victor Coscrato

Neurocomputing, 2020

Comparing two populations using Bayesian Fourier series density estimation.

[BibT_eX]

[DOI]

Luis Ernesto Salasar

Commun. Stat. Simul. Comput., 2020

MeLIME: Meaningful Local Explanation for Machine Learning Models.

[BibT_eX]

[DOI]

Frederik Hvilshøj

André C. P. L. F. de Carvalho

CoRR, 2020

CD-split: efficient conformal regions in high dimensions.

[BibT_eX]

[DOI]

CoRR, 2020

Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference.

[BibT_eX]

[DOI]

Astron. Comput., 2020

Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting.

[BibT_eX]

[DOI]

Niccolò Dalmasso

Ann B. Lee

Proceedings of the 37th International Conference on Machine Learning, 2020

Flexible distribution-free conditional predictive bands using density estimators.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Comparing probabilistic predictive models applied to football.

[BibT_eX]

[DOI]

J. Oper. Res. Soc., 2019

Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions.

[BibT_eX]

[DOI]

Afonso Fernandes Vaz

J. Mach. Learn. Res., 2019

Pragmatic Hypotheses in the Evolution of Science.

[BibT_eX]

[DOI]

Entropy, 2019

Distribution-free conditional predictive bands using density estimators.

[BibT_eX]

[DOI]

CoRR, 2019

NLS: an accurate and yet easy-to-interpret regression method.

[BibT_eX]

[DOI]

Victor Coscrato

CoRR, 2019

Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders.

[BibT_eX]

[DOI]

Bálint Gyires-Tóth

CoRR, 2019

Conditional independence testing: a predictive perspective.

[BibT_eX]

[DOI]

CoRR, 2019

Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space.

[BibT_eX]

[DOI]

André C. P. L. F. de Carvalho

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2017

Logically-consistent hypothesis testing and the hexagon of oppositions.

[BibT_eX]

[DOI]

Log. J. IGPL, 2017

2016

The Logical Consistency of Simultaneous Agnostic Hypothesis Tests.

[BibT_eX]

[DOI]

Entropy, 2016

2015

Logical consistency in simultaneous statistical test procedures.

[BibT_eX]

[DOI]

Luís Gustavo Esteves

Log. J. IGPL, 2015

A Bayesian Decision-Theoretic Approach to Logically-Consistent Hypothesis Testing.

[BibT_eX]

[DOI]

Gustavo Miranda da Silva

Entropy, 2015

2014

High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation.

[BibT_eX]

[DOI]

Ann B. Lee

Chad Schafer

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Learning with many experts: Model selection and sparsity.

[BibT_eX]

[DOI]