Data augmentation is commonly used to artificially inflate the size of training datasets and teach networks invariances to various transformations. For example, image classification networks often ...

Reproducibility is critical to any scientific endeavour, and machine learning is no exception. Releasing code that generates results from papers is an important step in addressing this, but difficu...