Julia algorithmic-differentiation Projects
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Optimization.jl
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
Project mention: SciPy: Interested in adopting PRIMA, but little appetite for more Fortran code | news.ycombinator.com | 2023-05-18Interesting response. I develop the Julia SciML organization https://sciml.ai/ and we'd be more than happy to work with you to get wrappers for PRIMA into Optimization.jl's general interface (https://docs.sciml.ai/Optimization/stable/). Please get in touch and we can figure out how to set this all up. I personally would be curious to try this out and do some benchmarks against nlopt methods.
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NBodySimulator.jl
A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
Julia algorithmic-differentiation related posts
Index
Project | Stars | |
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1 | Optimization.jl | 649 |
2 | NBodySimulator.jl | 123 |