Last Updated: 11 March 2021
Code Author: Alex J. Chan ([email protected])
An implementation of a transductive dropout network class can be found in models.py and a walkthrough of its use in an example regression problem is provided in tutorial.ipynb
This repo is pip installable - clone it, optionally create a virtual env, and install it (this will automatically install dependencies):
git clone https://github.com/XanderJC/transductive-dropout.git
cd transductive-dropout
pip install -e .Example usage:
from TD import transductive
# Get data somehow
X,y,unlabelled_X = get_data()
# Instantiate transductive dropout model
model = transductive([1,32,64,1], d_units=8)
# Train the model
model.train(X, y, unlabelled_X, iters=1000)If you use this software please cite as follows:
@inproceedings{chan2020unlabelled,
title={Unlabelled data improves {B}ayesian uncertainty calibration under covariate shift},
author={Alex James Chan and Ahmed Alaa and Zhaozhi Qian and Mihaela van der Schaar},
booktitle={International Conference on Machine Learning},
year={2020}
}