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Industry

Scientific Machine Learning, Differential Equations, High-Performance Computing

Language

Julia, Python, R

Features

numerical computing, scientific computing, machine learning, differentiable programming, modeling, business and industry, government, higher education research and training

SciML is an open source software organization created to unify the packages for scientific machine learning. This includes the development of modular scientific simulation support software, such as differential equation solvers, along with the methodologies for inverse problems and automated model discovery. By providing a diverse set of tools with a common interface, we provide a modular, easily-extendable, and highly performant ecosystem for handling a wide variety of scientific simulations.

SciML tools are used by many organizations, such as (but not limited to!) the CliMA: Climate Modeling Alliance, the
New York Federal Reserve Bank, the Julia Robotics community, Pumas-AI: Pharmaceutical Modeling and Simulation, and the Brazilian National Institute for Space Research (INPE).

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