91 citations · 581 across the 43 of their papers we have counts for
11 papers · 1 filter
NLS: an accurate and yet easy-to-interpret regression method
Victor Coscrato, Marco Henrique de Almeida Inácio, Tiago Botari +1
An important feature of successful supervised machine learning applications is to be able to explain the predictions given by the regression or classification model being used. How…
Flexible distribution-free conditional predictive bands using density estimators
Rafael Izbicki, Gilson T. Shimizu, Rafael B. Stern
Conformal methods create prediction bands that control average coverage under no assumptions besides i.i.d. data. Besides average coverage, one might also desire to control conditi…
Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders
Marco Henrique de Almeida Inácio, Rafael Izbicki, Bálint Gyires-Tóth
Given two distinct datasets, an important question is if they have arisen from the the same data generating function or alternatively how their data generating functions diverge fr…
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference
Niccolò Dalmasso, Taylor Pospisil, Ann B. Lee +3
It is well known in astronomy that propagating non-Gaussian prediction uncertainty in photometric redshift estimates is key to reducing bias in downstream cosmological analyses. Si…
Conditional independence testing: a predictive perspective
Marco Henrique de Almeida Inácio, Rafael Izbicki, Rafael Bassi Stern
Conditional independence testing is a key problem required by many machine learning and statistics tools. In particular, it is one way of evaluating the usefulness of some features…
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space
Tiago Botari, Rafael Izbicki, Andre C. P. L. F. de Carvalho
As machine learning becomes an important part of many real world applications affecting human lives, new requirements, besides high predictive accuracy, become important. One impor…
The NN-Stacking: Feature weighted linear stacking through neural networks
Victor Coscrato, Marco Henrique de Almeida Inácio, Rafael Izbicki
Stacking methods improve the prediction performance of regression models. A simple way to stack base regressions estimators is by combining them linearly, as done by \citet{breiman…
Teaching decision theory proof strategies using a crowdsourcing problem
Luis G. Esteves, Rafael Izbicki, Rafael B. Stern
Teaching how to derive minimax decision rules can be challenging because of the lack of examples that are simple enough to be used in the classroom. Motivated by this challenge, we…
Logically-consistent hypothesis testing in the hexagon of oppositions
Julio M. Stern, Luis G. Esteves, Rafael Izbicki +1
Although logical consistency is desirable in scientific research, standard statistical hypothesis tests are typically logically inconsistent. In order to address this issue, previo…
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations
Niccolò Dalmasso, Ann B. Lee, Rafael Izbicki +3
Complex phenomena in engineering and the sciences are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood does not exist…
Interpretable hypothesis tests
Victor Coscrato, Luís Gustavo Esteves, Rafael Izbicki +1
Although hypothesis tests play a prominent role in Science, their interpretation can be challenging. Three issues are (i) the difficulty in making an assertive decision based on th…