{"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/nengodl-combining-deep-learning-and","title":"NengoDL: Combining deep learning and neuromorphic modelling methods","arxiv_id":"1805.11144","date":"2018-05-28","proceeding":null,"authors":["Daniel Rasmussen"],"abstract":"NengoDL is a software framework designed to combine the strengths of\nneuromorphic modelling and deep learning. NengoDL allows users to construct\nbiologically detailed neural models, intermix those models with deep learning\nelements (such as convolutional networks), and then efficiently simulate those\nmodels in an easy-to-use, unified framework. In addition, NengoDL allows users\nto apply deep learning training methods to optimize the parameters of\nbiological neural models. In this paper we present basic usage examples,\nbenchmarking, and details on the key implementation elements of NengoDL. More\ndetails can be found at https://www.nengo.ai/nengo-dl .","url_abs":"http://arxiv.org/abs/1805.11144v3","url_pdf":"http://arxiv.org/pdf/1805.11144v3.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":"nengodl-combining-deep-learning-and","repo_url":"https://github.com/nengo/nengo-dl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.11144","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}