It has been observed that large-scale language models capture undesirable societal biases,
eg relating to race and gender; yet religious bias has been relatively unexplored. We …

Deep learning methods are a class of machine learning techniques capable of identifying
highly complex patterns in large datasets. Here, we provide a perspective and primer on deep …

Large language models, which are increasingly used in AI applications, display undesirable
stereotypes such as persistent associations between Muslims and violence. New …

Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

In order for machine learning to be trusted in many applications, it is critical to be able to
reliably explain why the machine learning algorithm makes certain predictions. For this reason, …

We present a new technique called contrastive principal component analysis (cPCA) that is
designed to discover low-dimensional structure that is unique to a dataset, or enriched in …

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing patient …

Echocardiography uses ultrasound technology to capture high temporal and spatial
resolution images of the heart and surrounding structures, and is the most common imaging …

Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial
resolution, making it possible to systematically link the morphology of cellular neighbourhoods …

Visualization and exploration of high-dimensional data is a ubiquitous challenge across
disciplines. Widely used techniques such as principal component analysis (PCA) aim to identify …