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20162022
most citedFlexible distribution-free conditional predictive bands using density estimators

24 citations · 67 across the 9 of their papers we have counts for

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7 papers · 1 filter

stat.ME2023

Spectral smooth tests for goodness-of-fit

Victor Candido Reis, Rafael Izbicki

Goodness-of-fit tests are crucial tools for assessing the validity of statistical models. In this paper, we introduce a novel approach, the Spectral Smooth Test (SST), that general…

stat.ME2021

Diagnostics for Conditional Density Models and Bayesian Inference Algorithms

David Zhao, Niccolò Dalmasso, Rafael Izbicki +1

There has been growing interest in the AI community for precise uncertainty quantification. Conditional density models f(y|x), where x represents potentially high-dimensional featu…

stat.ME2020

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

Niccolò Dalmasso, Rafael Izbicki, Ann B. Lee

Parameter estimation, statistical tests and confidence sets are the cornerstones of classical statistics that allow scientists to make inferences about the underlying process that…

stat.ME201924 cited

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…

stat.ME2019

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…

stat.ME20194 cited

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…