Paulo Orenstein

According to our database, Paulo Orenstein authored at least 13 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction.

Hannah Guan, Soukayna Mouatadid, Paulo Orenstein, Judah Cohen, Haiyu Dong, Zekun Ni, Jeremy Berman, Genevieve Flaspohler, Alex Lu, Jakob Schloer, Joshua Talib, Jonathan A. Weyn, Lester Mackey

CoRR, April, 2026

2025

Precipitation nowcasting of satellite data using physically-aligned neural networks.

Antônio Catão, Melvin Poveda, Leonardo Voltarelli, Paulo Orenstein

CoRR, November, 2025

2024

Split Conformal Prediction and Non-Exchangeable Data.

Roberto I. Oliveira, Paulo Orenstein, Thiago Ramos, João Vitor Romano

J. Mach. Learn. Res., 2024

BlockBoost: Scalable and Efficient Blocking through Boosting.

Thiago Ramos, Rodrigo Loro Schuller, Alex Akira Okuno, Lucas Nissenbaum, Roberto I. Oliveira, Paulo Orenstein

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Deep Hashing via Householder Quantization.

Lucas R. Schwengber, Lucas Resende, Paulo Orenstein, Roberto I. Oliveira

CoRR, 2023

SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AmnioML: Amniotic Fluid Segmentation and Volume Prediction with Uncertainty Quantification.

Daniel Csillag, Lucas Monteiro Paes, Thiago Ramos, João Vitor Romano, Rodrigo Schuller, Roberto de Beauclair Seixas, Roberto I. Oliveira, Paulo Orenstein

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Adaptive Bias Correction for Improved Subseasonal Forecasting.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey

CoRR, 2022

ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics.

Daniel Csillag, Carolina Piazza, Thiago Ramos, João Vitor Romano, Roberto I. Oliveira, Paulo Orenstein

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Learned Benchmarks for Subseasonal Forecasting.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey

CoRR, 2021

Online Learning with Optimism and Delay.

Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Scalable Approximate MCMC Algorithms for the Horseshoe Prior.

James E. Johndrow, Paulo Orenstein, Anirban Bhattacharya

J. Mach. Learn. Res., 2020

2019

Improving Subseasonal Forecasting in the Western U.S. with Machine Learning.

Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019