ricvolpi / generalize-unseen-domains

Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018

Code for the paper Generalizing to Unseen Domains via Adversarial Data Augmentation

Overview

Files

model.py: to build tf's graph

trainOps.py: to train/test

exp_configuration: config file with the hyperparameters

Prerequisites

Python 2.7, Tensorflow 1.6.0

How it works

To obtain MNIST and SVHN dataset, run

mkdir data
python download_and_process_mnist.py
sh download_svhn.sh

To train the model, run

sh run_exp.sh GPU_IDX

where GPU_IDX is the index of the GPU to be used.

Related work

If you are interested in the topic, you might also be interested in this (related repo here)