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Module kmath-noa

A Bayesian computation library over NOA together with relevant functionality from LibTorch.

Our aim is to cover a wide set of applications from particle physics simulations to deep learning. In fact, we support any differentiable program written on top of AutoGrad & ATen.

Installation

To install the library, you can simply publish to the local Maven repository:

./gradlew -q :kmath-noa:publishToMavenLocal

This will fetch and build native artifacts as well. Currently, we support only the GNU toolchain. For GPU kernels, we require a compatible CUDA installation. If you are on Windows, we recommend setting up everything on WSL.