Search Results for author:
Found 5 papers, 5 papers with code
Deep Hashing via Householder Quantization
Hashing is at the heart of large-scale image similarity search, and recent methods have been substantially improved through deep learning techniques.
Adaptive Bias Correction for Improved Subseasonal Forecasting
Subseasonal forecasting -- predicting temperature and precipitation 2 to 6 weeks ahead -- is critical for effective water allocation, wildfire management, and drought and flood mitigation.
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
To streamline this process and accelerate future development, we introduce SubseasonalClimateUSA, a curated dataset for training and benchmarking subseasonal forecasting models in the United States.
Online Learning with Optimism and Delay
Inspired by the demands of real-time climate and weather forecasting, we develop optimistic online learning algorithms that require no parameter tuning and have optimal regret guarantees under delayed feedback.
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
We hope that both our dataset and our methods will help to advance the state of the art in subseasonal forecasting.
