{"url":"/dataset/replication-data-for-online-learning-with","name":"Replication Data for: Online Learning with Optimism and Delay","full_name":null,"description_markdown":"The model forecasts for the sub-seasonal forecasting application considered in the Online Learning under Optimism and Delay paper experiments. This dataset consists of a single ZIP archive (919MB) that contains 1) a \"models\" folder that contains, for each model the forecasts for the Precip. 3-4w, Precip. 5-6w, Temp. 3-4w, Temp. 5-6w tasks on the western United States geography, and 2) a \"data\" folder that contains supporting geographic data. The data should be used to reproduce the PoolD experiments in https://github.com/geflaspohler/poold as described in the README. (2021-06-10)","description_withheld":null,"homepage":"https://doi.org/10.7910/DVN/IOCFCY","introduced_date":"2021-06-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/online-learning-with-optimism-and-delay","title":"Online Learning with Optimism and Delay","first_author":"Genevieve Flaspohler","url":null},"license":null,"modalities":[],"tasks":[{"name":"Weather Forecasting","url":"/task/weather-forecasting","datasets_with_task":"/datasets/task/weather-forecasting"},{"name":"Ensemble Learning","url":"/task/ensemble-learning","datasets_with_task":"/datasets/task/ensemble-learning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Replication Data for: Online Learning with Optimism and Delay"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}