Nonparametric Inference

Hierarchical clustering: visualization, feature importance and model selection
We propose methods for the analysis of hierarchical clustering that fully use the multi-resolution structure provided by a dendrogram. …
L. M. C. Cabezas, Rafael Izbicki, R. B. Stern
February, 2023 Applied Soft Computing Journal
Preprint
NLS: An accurate and yet easy-to-interpret prediction method
Over the last years, the predictive power of supervised machine learning (ML) has undergone impressive advances, achieving the status …
V. Coscrato, M. H. A. Inacio, T. Botari, Rafael Izbicki
January, 2023 Neural Networks
Preprint PDF
Likelihood-Free Frequentist Inference: Confidence Sets with Correct Conditional Coverage
Many areas of science make extensive use of computer simulators that implicitly encode likelihood functions of complex systems. …
N. Dalmasso, L. Masserano, D. Zhao, Rafael Izbicki, A. B. Lee
April, 2022 Submitted
PDF
Diagnostics for Conditional Density Models and Bayesian Inference Algorithms
D. Zhao, N. Dalmasso, Rafael Izbicki, A. B. Lee
September, 2021 Proceedings of Machine Learning Research (UAI Track) paper
PDF
Identifying Distributional Differences in Convective Evolution Prior to Rapid Intensification in Tropical Cyclones
Tropical cyclone (TC) intensity forecasts are issued by human forecasters who evaluate spatio-temporal observations (e.g., satellite …
T. McNeely, G. Vincent, Rafael Izbicki, K. M. Wood, A. B. Lee
February, 2021 Tackling Climate Change with Machine Learning workshop at NeurIPS 2021 (poster)
PDF