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Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
The paper introduces a novel approach to classifying events under generalized label shift by framing classification as hypothesis testing, which leads to valid uncertainty quantification. This is demonstrated through applications in biology and astroparticle physics.
L. Masserano, A. Shen, M. Doro, T. Dorigo, Rafael Izbicki, A. B. Lee
May, 2024 Proceedings of Machine Learning Research (ICML Track)
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Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference
Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes
V. Dheur, T. Bosser, Rafael Izbicki, S. Ben Taieb
February, 2024 Machine Learning
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Regression Trees for Fast and Adaptive Prediction Intervals
L. M. C. Cabezas, M. P. Otto, Rafael Izbicki, R. B. Stern
February, 2024 Information Sciences
Preprint PDF
Is augmentation effective in improving prediction in imbalanced datasets?
G. O. Assunção, Rafael Izbicki, M. O. Prates
February, 2024 Machine Learning
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Flexible conditional density estimation for time series
G. Grivol, Rafael Izbicki, A. A. Okuno, R. B. Stern
January, 2024 Brazilian Journal of Probability and Statistics
Preprint
The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts
L. Nakazono, R. R. Valença, G. Soares, Rafael Izbicki, Ž. Ivezić
January, 2024 Monthly Notices of the Royal Astronomical Society
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Detecting Distributional Differences in Labeled Sequence Data with Application to Tropical Cyclone Satellite Imagery
T. McNeely, G. Vincente, K. M. Wood, Rafael Izbicki, A. B. Lee
August, 2023 Annals of Applied Statistics
Preprint PDF
Classification under Prior Probability Shift in Simulator-Based Inference: Application to Atmospheric Cosmic-Ray Showers
A. Shen, L. Masserano, Rafael Izbicki, T. Dorigo, M. Doro, A. B. Lee
March, 2023 NeurIPS (Machine Learning and the Physical Sciences Workshop; Best Poster Award)
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A unified framework for dataset shift diagnostics
F. M. Polo, Rafael Izbicki, E. G. Lacerda Jr, J. P. Ibieta-Jimenez, R. Vicente
March, 2023 Information Sciences
Preprint
Simulation-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems
L. Masserano, T. Dorigo, Rafael Izbicki, M. Kuusela, A. B. Lee
February, 2023 Proceedings of Machine Learning Research (AISTATS track)
Preprint PDF