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Awesome GitHub RepositoriesGradient Calculation Tools
APIs for computing gradients and Jacobians using automatic differentiation.
Distinguishing note: Focuses on the API surface for numerical differentiation, distinct from the underlying engine.
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- jax-ml/jax
jax-ml/jax
34,919View on GitHubThis project is a high-performance numerical computing library designed for large-scale scientific and machine learning workloads. It functions as an automatic differentiation framework and a just-in-time compilation engine, transforming high-level Python code into optimized machine instructions. By enforcing pure functional programming patterns and immutable array semantics, the library ensures that mathematical functions remain compatible with automated graph transformations and symbolic differentiation. The platform distinguishes itself through its distributed array computing capabilities,
Computes gradients and Jacobians using automatic differentiation to support efficient numerical workflows.
Pythonjax
