Generative adversarial networks (GANs) are a popular learning framework to model the underlying distribution of images. GANs comprise a min-max game between the generator and the discriminator. While the generator transforms ...

Deep Neural Networks achieve near-human performance on several benchmark datasets, yet they are not as robust as humans. Their success relies on the proximity of test samples to the distribution of training data, resulting ...

Medical imaging provides a non-invasive way to visualize tissues and diseases, enabling both qualitative and quantitative assessments that are needed in diagnosing and monitoring a wide range of conditions. Modalities ...