{"url":"/method/adarnn","slug":"adarnn","name":"AdaRNN","full_name":"AdaRNN","full_name_withheld":false,"description_markdown":"**AdaRNN** is an adaptive [RNN](https://paperswithcode.com/methods/category/recurrent-neural-networks) that learns an adaptive model through two modules: [Temporal Distribution Characterization](https://paperswithcode.com/method/temporal-distribution-characterization) (TDC) and [Temporal Distribution Matching](https://paperswithcode.com/method/temporal-distribution-matching) (TDM) algorithms. Firstly, to better characterize the distribution information in time-series, TDC splits the training data into $K$ most diverse periods that have a large distribution gap inspired by the principle of maximum entropy. After that, a temporal distribution matching (TDM) algorithm is used to dynamically reduce distribution divergence using a [RNN](https://paperswithcode.com/methods/category/recurrent-neural-networks)-based model.","description_state":"present","introduced_year":null,"introduced_by":{"title":"AdaRNN: Adaptive Learning and Forecasting of Time Series","paper":"/paper/adarnn-adaptive-learning-and-forecasting-of","first_author":"Yuntao Du","n_authors":7,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/adarnn-adaptive-learning-and-forecasting-of"},"source":{"url":"https://arxiv.org/abs/2108.04443v2","title":"AdaRNN: Adaptive Learning and Forecasting of Time Series","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Sequential","area_id":"sequential","collection":"Recurrent Neural Networks","url":"/methods/category/recurrent-neural-networks","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/adarnn-adaptive-learning-and-forecasting-of","title":"AdaRNN: Adaptive Learning and Forecasting of Time Series","date":"2021-08-10","arxiv_id":"2108.04443","n_code_links":2,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/activity-recognition","name":"Activity Recognition","papers":1},{"task":"/task/financial-analysis","name":"Financial Analysis","papers":1},{"task":"/task/human-activity-recognition","name":"Human Activity Recognition","papers":1},{"task":"/task/time-series-1","name":"Time Series","papers":1},{"task":"/task/time-series","name":"Time Series Analysis","papers":1}],"tasks_shown":5,"n_tasks":5,"usage_by_year":[{"year":"2021","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/adarnn"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}