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# Module kmath-noa
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This module provides a `kotlin-jvm` frontend for the
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A Bayesian computation library over
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[NOA](https://github.com/grinisrit/noa.git)
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library together with relevant functionality from
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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 create a Bayesian computational platform
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which covers a wide set of applications from particle physics
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simulations to deep learning and general differentiable programs
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written on top of `AutoGrad` & `ATen`.
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Our aim is to cover a wide set of applications from particle physics
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simulations to deep learning. 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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## Installation
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## Artifact:
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The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-13`.
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The Maven coordinates of this project are `space.kscience:kmath-tensors:0.3.0-dev-14`.
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**Gradle:**
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```gradle
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}
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dependencies {
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implementation 'space.kscience:kmath-tensors:0.3.0-dev-13'
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implementation 'space.kscience:kmath-tensors:0.3.0-dev-14'
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}
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```
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**Gradle Kotlin DSL:**
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}
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dependencies {
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implementation("space.kscience:kmath-tensors:0.3.0-dev-13")
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implementation("space.kscience:kmath-tensors:0.3.0-dev-14")
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}
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```
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