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SciML is an open-source software for scientific machine learning, physics-informed AI, and differentiable programming. It provides a unified ecosystem of composable tools for differential equations, inverse problems, and automated model discovery.
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About
SciML is an open-source software ecosystem dedicated to scientific machine learning, physics-informed AI, and differentiable programming. It offers a unified and composable set of tools for solving complex scientific problems, including differential equations (ODEs, SDEs, DDEs, DAEs), large-scale nonlinear systems, and inverse problems. The platform facilitates automated model discovery and integrates with machine learning frameworks through differentiability. Built primarily with Julia, SciML emphasizes robust and performant algorithms, achieving state-of-the-art results. It also provides bridges to Python and R, ensuring broad accessibility for the scientific community. Key features include advanced equation solvers, physics-informed model discovery, and ML-assisted tooling for model acceleration, all supported by a large and active developer community.
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Open Source
Not publicly disclosed. Check sciml.ai for current pricing.
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