{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/prediction-under-uncertainty-with-error","title":"Prediction Under Uncertainty with Error-Encoding Networks","arxiv_id":"1711.04994","date":"2017-11-14","proceeding":null,"authors":["Mikael Henaff","Junbo Zhao","Yann Lecun"],"abstract":"In this work we introduce a new framework for performing temporal predictions\nin the presence of uncertainty. It is based on a simple idea of disentangling\ncomponents of the future state which are predictable from those which are\ninherently unpredictable, and encoding the unpredictable components into a\nlow-dimensional latent variable which is fed into a forward model. Our method\nuses a supervised training objective which is fast and easy to train. We\nevaluate it in the context of video prediction on multiple datasets and show\nthat it is able to consistently generate diverse predictions without the need\nfor alternating minimization over a latent space or adversarial training.","url_abs":"http://arxiv.org/abs/1711.04994v3","url_pdf":"http://arxiv.org/pdf/1711.04994v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"prediction-under-uncertainty-with-error","repo_url":"https://github.com/mbhenaff/EEN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"video-prediction","task_name":"Video Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1711.04994","atlas_url":"https://app.syntology.ai/?focus=1711.04994","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}