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# Module kmath-noa
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A general purpose differentiable computation library over
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A general purpose differentiable programming library over
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[NOA](https://github.com/grinisrit/noa.git)
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together with relevant functionality from
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[LibTorch](https://pytorch.org/cppdocs).
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Our aim is to cover a wide set of applications
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from bayesian optimisation and deep learning to particle physics
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from bayesian computation and deep learning to particle physics
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simulations. In fact, we support any
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differentiable program written on top of
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`AutoGrad` & `ATen`.
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