machine learning

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)
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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
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A new LDA formulation with covariates
G. Shimizu, Rafael Izbicki, D. Valle
January, 2023 Communications in Statistics - Simulation and Computation
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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, 2022 Annals of Applied Statistics
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CD-split and HPD-split: Efficient conformal regions in high dimensions
Conformal methods create prediction bands that control average coverage assuming solely i.i.d. data. We introduce CD-split and HPD-split, which yield general prediction regions and converge to the optimal highest predictive density set.
Rafael Izbicki, Gilson Shimizu, Rafael B. Stern
May, 2022 Journal of Machine Learning Research
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CD-split and HPD-split: Efficient conformal regions in high dimensions
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
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Causas de desaparecimento no estado de São Paulo entre 2013 e 2014: uma análise automatizada de boletins de ocorrência
Este artigo estuda as causas de desaparecimento no estado de São Paulo por idade e sexo dos desaparecidos. Para tanto, utiliza algoritmos de aprendizado de máquina para avaliar automaticamente o texto de boletins de ocorrência.
Mateus B. Comito, Rafael Izbicki, Rafael B. Stern, Julio A. Z. Trecenti
February, 2021 In RDPESP
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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)
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The Latent Dirichlet Allocation model with covariates (LDAcov): a case study on the effect of fire on species composition in Amazonian forests
Understanding and predicting the effect of global change phenomena on biodiversity is challenging given that biodiversity data are …
D. Valle, G. Shimizu, Rafael Izbicki, L. Maracahipes, D. Silvério, L. Paolucci, Y. Jameel, P. Brando
February, 2021 Ecology and Evolution
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Distance assessment and analysis of high-dimensional samples using variational autoencoders
An important question in many machine learning applications is whether two samples arise from the same generating distribution. …
M. H. de A. Inácio, Rafael Izbicki, B. Gyires-Tóth
January, 2021 Information Sciences
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