https://github.com/yixuan/almond
ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion
https://github.com/yixuan/almond
deep-learning langevin-diffusion latent-variable-models machine-learning neural-networks
Last synced: 12 months ago
JSON representation
ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion
- Host: GitHub
- URL: https://github.com/yixuan/almond
- Owner: yixuan
- License: mit
- Created: 2019-11-04T02:00:36.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-11-16T23:47:13.000Z (over 6 years ago)
- Last Synced: 2025-07-15T05:13:45.776Z (12 months ago)
- Topics: deep-learning, langevin-diffusion, latent-variable-models, machine-learning, neural-networks
- Language: Python
- Homepage:
- Size: 2.38 MB
- Stars: 13
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
## ALMOND 
This repository stores the code files for the article
"[ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion](https://doi.org/10.1080/01621459.2019.1691563)".
### Installation
ALMOND depends on the [MXNet](https://mxnet.incubator.apache.org/) deep learning framework.
First install a proper version of MXNet following the
[official documentation](https://mxnet.incubator.apache.org/get_started), for example:
```bash
pip install mxnet --user
```
And then enter the `package` directory and run
```bash
cd package
python3 setup install --user
```
### Running Examples
The `experiments` directory contains the code files for all numerical experiments in the
article. Simply run the Python/R files in order in each subdirectory. `results` contains
the generated plots used by the article.
### License
The `almond` Python package and the experiment code files are under the MIT License.