https://github.com/rylanschaeffer/fietelab-dynamical-crp

Code for CoLLAs 2022 paper Streaming Inference for Infinite Nonstationary Clustering
https://github.com/rylanschaeffer/fietelab-dynamical-crp

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Code for CoLLAs 2022 paper Streaming Inference for Infinite Nonstationary Clustering

• Host: GitHub
• URL: https://github.com/rylanschaeffer/fietelab-dynamical-crp
• Owner: RylanSchaeffer
• Created: 2021-10-29T04:47:17.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2022-04-27T21:58:21.000Z (over 2 years ago)
• Last Synced: 2024-10-12T21:12:58.311Z (about 1 month ago)
• Language: Python
• Homepage:
• Size: 4.85 MB
• Stars: 0
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Streaming Inference for Infinite Non-Stationary Clustering

### Authors: Rylan Schaeffer, Gabrielle Kaili-May Liu, Yilun Du, Ila Rani Fiete

-----

This code corresponds to our .

## Setup

After cloning the repository, create a virtual environment for Python 3:

`python3 -m venv dcrp_venv`

Then activate the virtual environment:

`source dcrp_venv/bin/activate`

Ensure pip is up to date:

`pip install --upgrade pip`

Then install the required packages:

`pip install -r requirements.txt`

We did not test Python2, but Python2 may work.

## Running

Each experiment (e.g. `00_prior`) is in its own directory. Each experiment directory should contain a 

`run_one.py` file for running a single configuration. If you want to launch sweeps, 

we run sweeps via [Weights and Biases](https://wandb.ai/) that we configure via `.yaml` files. 

After completing your runs, each experiment directory should also contain an `analyze_sweep.py`

file that reads the results from Weights and Biases and generates the plots in a `plots`

subdirectory (e.g. `00_prior/plots`).

## Contact

Questions? Comments? Interested in collaborating? Open an issue or 

email Rylan Schaeffer ([email protected]) and cc Ila Fiete ([email protected]).