Hellow guys, Welcome to my website, and you are watching The Julia SciML Ecosystem: Scientific Machine Learning as a Software Problem - Chris Rackauckas. and this vIdeo is uploaded by The Julia Programming Language at 2021-03-09T08:11:01-08:00. We are pramote this video only for entertainment and educational perpose only. So, I hop you like our website.
| Name | The Julia SciML Ecosystem: Scientific Machine Learning as a Software Problem - Chris Rackauckas |
| Video Uploader | Video From The Julia Programming Language |
| Upload Date | This Video Uploaded At 09-03-2021 16:11:01 |
| Video Discription | The Julia SciML Ecosystem: Scientific Machine Learning as a Software Problem Christopher V. Rackauckas, Massachusetts Institute of Technology Abstract: The Julia SciML ecosystem is a software suite for high performance modeling and simulation which incorporates scientific machine learning for automated model discovery and nonlinear model order reduction. This talk will introduce the audience to the philosophy of composability of the software suite by demonstrating how connections between seemingly disjoint modules can be composed to create new high performance algorithms on demand. It will start by describing the high performance simulation techniques, from new methods for numerically approximating ODEs and SDEs to all the way to methods for generating discretizations for nonlinear optimal control and automated solution of partial differential equations. From there connections to machine learning will be seen, with physics-informed neural networks (PINNs) supplementing the suite with non-local partial differential-algebraic equation solvers to universal differential equations with the ability to learn model misspecification directly from data. Connections to probabilistic programming will be discussed, mixing Bayesian estimation with scientific machine learning, along with high performance computing via CPU and GPU parallelism. This talk will thus set the stage for the following speakers who will demonstrate specific methodologies and applications within this application sphere. For more information on the SciML Open Source Scientific Machine Learning Software Ecosystem, see https://sciml.ai/. For more info on the Julia Programming Language, follow us on Twitter: https://twitter.com/JuliaLanguage Contents 00:00 Overview 00:21 Objective: The aim of the SciML ecosystem 01:24 Definition: What is scientific machine learning 02:45 Example: An application to ocean columns modelling 07:25 Hard Problem: How to fit a neural network inside a simulator 10:59 No Silver Bullet: Different adjoint methods for different problems 13:24 SciML vs. The Rest: A comparison with other libraries in other languages 14:38 SciML Today: The current state of the SciML ecosystem 15:35 Conclusion: Further developments S/O to https://github.com/pitmonticone for the video timestamps! Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/YouTubeVideoTimestamps Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/YouTubeVideoSubtitles |
| Category | Science & Technology |
| Tags | Julia | Language | Programming | programming | JuliaLang | coding | learn to code | Julia Language | ML | Machine Learning | anyone can code | tutorials | Julia programming | The Julia Programming Language |
