https://github.com/zalandoresearch/jaxrk

RKHS feature vectors, operators, and statistical models using JAX for automatic differentiation
https://github.com/zalandoresearch/jaxrk

Last synced: about 1 month ago
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RKHS feature vectors, operators, and statistical models using JAX for automatic differentiation

• Host: GitHub
• URL: https://github.com/zalandoresearch/jaxrk
• Owner: zalandoresearch
• License: mit
• Created: 2020-04-01T06:30:40.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2021-06-11T13:08:17.000Z (over 3 years ago)
• Last Synced: 2024-11-07T14:04:53.739Z (about 1 month ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 5.07 MB
• Stars: 8
• Watchers: 6
• Forks: 3
• Open Issues: 12
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# JaxRK

JaxRK is a library for working with (vectors of) RKHS elements and RKHS operators using [JAX](https://github.com/google/jax) for automatic differentiation. This library includes implementations of [kernel transfer operators](https://arxiv.org/abs/1712.01572) and [conditional density operators](https://arxiv.org/abs/1905.11255).

## Installation

First you have to make sure to have jax and jaxlib installed. Please follow the [JAX installation instructions](https://github.com/google/jax) depending on whether you want a CPU or GPU/TPU installation. After that you only need

```

$ pip install jaxrk

```

## Quick start examples

For some examples of what you can do with JaxRK, see [examples/Quick_start.ipynb](https://github.com/zalandoresearch/JaxRK/blob/master/examples/Quick_start.ipynb).

## Development

To help in developing JaxRK, clone the github repo and change to the cloned directory on the command line. Then 

```

$ pip install -e .

$ pytest tests/

```

will install the package into your python path. Changes to files in the directory are reflected in the python package when loaded.