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Awesome GitHub RepositoriesAutomatic Differentiation Frameworks
Engines for computing exact gradients and higher-order derivatives.
Distinguishing note: Provides a comprehensive engine for differentiation, distinct from specific utility functions.
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Awesome Automatic Differentiation Frameworks GitHub Repositories
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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 exact gradients and higher-order derivatives of complex functions using both forward and reverse modes.
Pythonjax
