{"url":"/method/re-net","slug":"re-net","name":"RE-NET","full_name":"Recurrent Event Network","full_name_withheld":false,"description_markdown":"Recurrent Event Network (RE-NET) is an autoregressive architecture for predicting future interactions. The occurrence of a fact (event) is modeled as a probability distribution conditioned on temporal sequences of past knowledge graphs. RE-NET employs a recurrent event encoder to encode past facts and uses a neighborhood aggregator to model the connection of facts at the same timestamp. Future facts can then be inferred in a sequential manner based on the two modules.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs","paper":"/paper/recurrent-event-network-for-reasoning-over","first_author":"Woojeong Jin","n_authors":4,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/recurrent-event-network-for-reasoning-over"},"source":{"url":"https://arxiv.org/abs/1904.05530v4","title":"Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Graphs","area_id":"graphs","collection":"Graph Models","url":"/methods/category/graph-models","pwc_aliases":[]}],"n_papers_tagged":2,"archive_num_papers":2,"papers_newest_first":[{"paper":null,"title":"Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs","date":"2020-11-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/recurrent-event-network-for-reasoning-over","title":"Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs","date":"2019-04-11","arxiv_id":"1904.05530","n_code_links":2,"syntology":null}],"papers_shown":2,"tasks":[{"task":"/task/knowledge-graphs","name":"Knowledge Graphs","papers":2},{"task":"/task/link-prediction","name":"Link Prediction","papers":2},{"task":"/task/temporal-sequences","name":"Temporal Sequences","papers":2}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2019","papers":1},{"year":"2020","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/re-net"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}