{"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/learning-to-reason-with-third-order-tensor-1","title":"Learning to Reason with Third Order Tensor Products","arxiv_id":null,"date":"2018-12-01","proceeding":"NeurIPS 2018 12","authors":["Imanol Schlag","Jürgen Schmidhuber"],"abstract":"We combine Recurrent Neural Networks with Tensor Product Representations to\nlearn combinatorial representations of sequential data. This improves symbolic\ninterpretation and systematic generalisation. Our architecture is trained end-to-end\nthrough gradient descent on a variety of simple natural language reasoning tasks,\nsignificantly outperforming the latest state-of-the-art models in single-task and\nall-tasks settings. We also augment a subset of the data such that training and test\ndata exhibit large systematic differences and show that our approach generalises\nbetter than the previous state-of-the-art.","url_abs":"http://papers.nips.cc/paper/8203-learning-to-reason-with-third-order-tensor-products","url_pdf":"http://papers.nips.cc/paper/8203-learning-to-reason-with-third-order-tensor-products.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":"learning-to-reason-with-third-order-tensor-1","repo_url":"https://github.com/ischlag/TPR-RNN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}