{"url":"/task/correlated-time-series-forecasting","name":"Correlated Time Series Forecasting","slug":"correlated-time-series-forecasting","description_markdown":null,"categories":[{"name":"Time Series","url":"/area/time-series"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":10,"papers_with_code":4,"benchmarks":4,"benchmark_tables_in_archive":4,"benchmark_tables_shown":4,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":8,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/correlated-time-series-forecasting-on","slug":"correlated-time-series-forecasting-on","dataset":"Electricity","dataset_url":"/dataset/electricity","rows_in_archive":1,"metrics":["FLOPs(M)","Parameters(K)"],"first_row_in_archive_order":{"model":"LightCTS","paper_title":"LightCTS: A Lightweight Framework for Correlated Time Series Forecasting","paper_url":"/paper/lightcts-a-lightweight-framework-for","paper_date":"2023-02-23","arxiv_id":"2302.11974","code_links":[{"title":"ai4cts/lightcts","url":"https://github.com/ai4cts/lightcts"}],"syntology":null}},{"leaderboard":"/sota/correlated-time-series-forecasting-on-metr-la","slug":"correlated-time-series-forecasting-on-metr-la","dataset":"METR-LA","dataset_url":"/dataset/metr-la","rows_in_archive":1,"metrics":["FLOPs(M)","MAE @ 12 step","MAPE @ 12 step","Parameters(K)","RMSE @ 12 step"],"first_row_in_archive_order":{"model":"LightCTS","paper_title":"LightCTS: A Lightweight Framework for Correlated Time Series Forecasting","paper_url":"/paper/lightcts-a-lightweight-framework-for","paper_date":"2023-02-23","arxiv_id":"2302.11974","code_links":[{"title":"ai4cts/lightcts","url":"https://github.com/ai4cts/lightcts"}],"syntology":null}},{"leaderboard":"/sota/correlated-time-series-forecasting-on-pems","slug":"correlated-time-series-forecasting-on-pems","dataset":"PEMS-BAY","dataset_url":"/dataset/pems-bay","rows_in_archive":1,"metrics":["FLOPs(M)","MAE @ 12 step","MAPE @ 12 step","Parameters(K)","RMSE @ 12 step"],"first_row_in_archive_order":{"model":"LightCTS","paper_title":"LightCTS: A Lightweight Framework for Correlated Time Series Forecasting","paper_url":"/paper/lightcts-a-lightweight-framework-for","paper_date":"2023-02-23","arxiv_id":"2302.11974","code_links":[{"title":"ai4cts/lightcts","url":"https://github.com/ai4cts/lightcts"}],"syntology":null}},{"leaderboard":"/sota/correlated-time-series-forecasting-on-solar","slug":"correlated-time-series-forecasting-on-solar","dataset":"Solar-Power","dataset_url":"/dataset/solar-power","rows_in_archive":1,"metrics":["FLOPs(M)","Parameters(K)"],"first_row_in_archive_order":{"model":"LightCTS","paper_title":"LightCTS: A Lightweight Framework for Correlated Time Series Forecasting","paper_url":"/paper/lightcts-a-lightweight-framework-for","paper_date":"2023-02-23","arxiv_id":"2302.11974","code_links":[{"title":"ai4cts/lightcts","url":"https://github.com/ai4cts/lightcts"}],"syntology":null}}],"datasets":[{"url":"/dataset/pemsd8","name":"PeMSD8","full_name":"","num_papers_in_archive":44},{"url":"/dataset/pems04","name":"PeMS04","full_name":"","num_papers_in_archive":37},{"url":"/dataset/metr-la","name":"METR-LA","full_name":"","num_papers_in_archive":36},{"url":"/dataset/pems-bay","name":"PEMS-BAY","full_name":"","num_papers_in_archive":34},{"url":"/dataset/electricity","name":"Electricity","full_name":"Individual household electric power consumption Data Set","num_papers_in_archive":32},{"url":"/dataset/pemsd7","name":"PeMSD7","full_name":"","num_papers_in_archive":26},{"url":"/dataset/pems07","name":"PeMS07","full_name":"","num_papers_in_archive":25},{"url":"/dataset/solar-power","name":"Solar-Power","full_name":"Solar Power Data for Integration Studies (Alabama)","num_papers_in_archive":4}],"subtasks":[],"parent_tasks":[{"url":"/task/time-series-forecasting","name":"Time Series Forecasting"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":4,"of":4,"tagged_in_all":10,"items":[{"url":"/paper/temporal-query-network-for-efficient","title":"Temporal Query Network for Efficient Multivariate Time Series Forecasting","date":"2025-05-19","arxiv_id":"2505.12917","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/correlated-time-series-self-supervised","title":"Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping","date":"2023-06-12","arxiv_id":"2306.06994","repositories_listed":1,"syntology":null},{"url":"/paper/lightcts-a-lightweight-framework-for","title":"LightCTS: A Lightweight Framework for Correlated Time Series Forecasting","date":"2023-02-23","arxiv_id":"2302.11974","repositories_listed":1,"syntology":null},{"url":"/paper/a-novel-deep-learning-model-for-hotel-demand","title":"A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19","date":"2022-03-08","arxiv_id":"2203.04383","repositories_listed":1,"syntology":null}],"syntology_records":1,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}