{"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/embed-to-control-a-locally-linear-latent","title":"Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images","arxiv_id":"1506.07365","date":"2015-06-24","proceeding":"NeurIPS 2015 12","authors":["Manuel Watter","Jost Tobias Springenberg","Joschka Boedecker","Martin Riedmiller"],"abstract":"We introduce Embed to Control (E2C), a method for model learning and control\nof non-linear dynamical systems from raw pixel images. E2C consists of a deep\ngenerative model, belonging to the family of variational autoencoders, that\nlearns to generate image trajectories from a latent space in which the dynamics\nis constrained to be locally linear. Our model is derived directly from an\noptimal control formulation in latent space, supports long-term prediction of\nimage sequences and exhibits strong performance on a variety of complex control\nproblems.","url_abs":"http://arxiv.org/abs/1506.07365v3","url_pdf":"http://arxiv.org/pdf/1506.07365v3.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":"embed-to-control-a-locally-linear-latent","repo_url":"https://github.com/RoboticsDesignLab/jitterbug","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1506.07365","atlas_url":"https://app.syntology.ai/?focus=1506.07365","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}