The Shifts Dataset is a dataset for evaluation of uncertainty estimates and robustness to distributional shift. The dataset, which has been collected from industrial sources and services, is composed of three tasks, with each corresponding to a particular data modality: tabular weather prediction, machine translation, and self-driving car (SDC) vehicle motion prediction. All of these data modalities and tasks are affected by real, `in-the-wild' distributional shifts and pose interesting challenges with respect to uncertainty estimation.
46 PAPERS • 1 BENCHMARK
A multivariate spatio-temporal benchmark dataset for meteorological forecasting based on real-time observation data from ground weather stations.
8 PAPERS • 16 BENCHMARKS
IowaRain is a dataset of rainfall events for the state of Iowa (2016-2019) acquired from the National Weather Service Next Generation Weather Radar (NEXRAD) system and processed by a quantitative precipitation estimation system. The dataset presented in this study could be used for better disaster monitoring, response and recovery by paving the way for both predictive and prescriptive modeling
4 PAPERS • NO BENCHMARKS YET
A new spatio-temporal benchmark dataset (Hurricane), is suited for forecasting during extreme events and anomalies. The dataset is provided through the Florida Department of Revenue which provides the monthly sales revenue (2003-2020) for the tourism industry for all 67 counties of Florida which are prone to annual hurricanes. Furthermore, we aligned and joined the raw time series with the history of hurricane categories based on time for each county. More precisely, the hurricane category indicates the maximum sustained wind speed which can result in catastrophic damages (Oceanic 2022).
2 PAPERS • 1 BENCHMARK