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Showing 2 open source projects for "numerical"
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JAX
Composable transformations of Python+NumPy programs
With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and... -
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AiGfxLab is a powerful open source image processing application for Windows. The plugin architecture permits both general-purpose and specialized processing, with an emphasis on intuitive GUI, numerical accuracy, maximal extensibility and customization.
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