bnn_chaos_model

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bnn_chaos_model

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Model and training code for Bayesian neural network for compact planetary instability

// repository documentation

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# [A Bayesian neural network predicts the dissolution of compact planetary systems](https://arxiv.org/abs/2101.04117)

This repository is the official implementation of the paper https://arxiv.org/abs/2101.04117,
containing training code, evaluation scripts, and figure generation.

For an easy-to-use API implementing
a trained version of this model, check out [spock](https://github.com/dtamayo/spock)!

![](https://raw.githubusercontent.com/MilesCranmer/bnn_chaos_model/master/orbital_dynamics_model-01.png)

# Running

To train the model, download the data into the `/data` folder
from this [Globus link](https://app.globus.org/file-manager?origin_id=ae09b8a8-5040-11eb-a4d1-0a53a3613b81&origin_path=%2F).

Run the script `train.sh`, which will train
the model 30 times from different seeds.

To generate the figures, edit the `figures/generate.sh` script
to have `true` instead of `false` for any figure you'd like to generate.
Then, execute that script in the folder.

# Requirements

One can install a working conda environment from the `environment.yml` file:

```bash
conda env create -f environment.yml
```

**Note**: You may need to delete the line:
```yml
  - conda-forge::cudatoolkit=10.1
```
from the `environment.yml` file depending on your system setup.

**Note 2**: On Apple Silicon, in addition to the above change, you will also
need to run the `env create` command with `CONDA_SUBDIR=osx-64` as
an environment variable. This is because some of the specific dependencies are
not available for Apple Silicon yet.

bnn_chaos_model

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