{"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/fashionable-modelling-with-flux","title":"Fashionable Modelling with Flux","arxiv_id":"1811.01457","date":"2018-11-01","proceeding":null,"authors":["Michael Innes","Elliot Saba","Keno Fischer","Dhairya Gandhi","Marco Concetto Rudilosso","Neethu Mariya Joy","Tejan Karmali","Avik Pal","Viral Shah"],"abstract":"Machine learning as a discipline has seen an incredible surge of interest in\nrecent years due in large part to a perfect storm of new theory, superior\ntooling, renewed interest in its capabilities. We present in this paper a\nframework named Flux that shows how further refinement of the core ideas of\nmachine learning, built upon the foundation of the Julia programming language,\ncan yield an environment that is simple, easily modifiable, and performant. We\ndetail the fundamental principles of Flux as a framework for differentiable\nprogramming, give examples of models that are implemented within Flux to\ndisplay many of the language and framework-level features that contribute to\nits ease of use and high productivity, display internal compiler techniques\nused to enable the acceleration and performance that lies at the heart of Flux,\nand finally give an overview of the larger ecosystem that Flux fits inside of.","url_abs":"http://arxiv.org/abs/1811.01457v3","url_pdf":"http://arxiv.org/pdf/1811.01457v3.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":"fashionable-modelling-with-flux","repo_url":"https://github.com/FluxML/Flux.jl","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"fashionable-modelling-with-flux","repo_url":"https://github.com/storopoli/Computacao-Cientifica","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"CC-BY-SA-4.0"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1811.01457","atlas_url":"https://app.syntology.ai/?focus=1811.01457","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}