{"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/diffeqfluxjl-a-julia-library-for-neural","title":"DiffEqFlux.jl - A Julia Library for Neural Differential Equations","arxiv_id":"1902.02376","date":"2019-02-06","proceeding":null,"authors":["Chris Rackauckas","Mike Innes","Yingbo Ma","Jesse Bettencourt","Lyndon White","Vaibhav Dixit"],"abstract":"DiffEqFlux.jl is a library for fusing neural networks and differential\nequations. In this work we describe differential equations from the viewpoint\nof data science and discuss the complementary nature between machine learning\nmodels and differential equations. We demonstrate the ability to incorporate\nDifferentialEquations.jl-defined differential equation problems into a\nFlux-defined neural network, and vice versa. The advantages of being able to\nuse the entire DifferentialEquations.jl suite for this purpose is demonstrated\nby counter examples where simple integration strategies fail, but the\nsophisticated integration strategies provided by the DifferentialEquations.jl\nlibrary succeed. This is followed by a demonstration of delay differential\nequations and stochastic differential equations inside of neural networks. We\nshow high-level functionality for defining neural ordinary differential\nequations (neural networks embedded into the differential equation) and\ndescribe the extra models in the Flux model zoo which includes neural\nstochastic differential equations. We conclude by discussing the various\nadjoint methods used for backpropogation of the differential equation solvers.\nDiffEqFlux.jl is an important contribution to the area, as it allows the full\nweight of the differential equation solvers developed from decades of research\nin the scientific computing field to be readily applied to the challenges posed\nby machine learning and data science.","url_abs":"http://arxiv.org/abs/1902.02376v1","url_pdf":"http://arxiv.org/pdf/1902.02376v1.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":"diffeqfluxjl-a-julia-library-for-neural","repo_url":"https://github.com/SciML/DiffEqFlux.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"diffeqfluxjl-a-julia-library-for-neural","repo_url":"https://github.com/UnofficialJuliaMirror/DiffEqFlux.jl-aae7a2af-3d4f-5e19-a356-7da93b79d9d0","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"diffeqfluxjl-a-julia-library-for-neural","repo_url":"https://github.com/UnofficialJuliaMirrorSnapshots/DiffEqFlux.jl-aae7a2af-3d4f-5e19-a356-7da93b79d9d0","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"diffeqfluxjl-a-julia-library-for-neural","repo_url":"https://github.com/ali-ramadhan/6S898-climate-parameterization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"diffeqfluxjl-a-julia-library-for-neural","repo_url":"https://github.com/ali-ramadhan/neural-differential-equation-climate-parameterizations","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1902.02376","atlas_url":"https://app.syntology.ai/?focus=1902.02376","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}