Today's state-of-the-art machine vision models are vulnerable to image corruptions like
blurring or compression artefacts, limiting their performance in many real-world applications …

Unsupervised domain adaptation (UDA) aims to transfer knowledge from a related but
different well-labeled source domain to a new unlabeled target domain. Most existing UDA …

State-of-the-art deep learning models are often trained with a large amount of costly labeled
training data. However, requiring exhaustive manual annotations may degrade the model's …

Deep learning applications have been thriving over the last decade in many different
domains, including computer vision and natural language understanding. The drivers for the …