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README.md

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)

About

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

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