Bayesian Inference and Representations in the Age of Foundation Models

From theory to prototypes in just 72 hours: our recent research retreat brought together interdisciplinary teams to explore the future of probabilistic deep learning. Over several days, participants engaged with key challenges at the intersection of machine learning, statistics, and domain science, ranging from sparsity and structure in neural representations to Bayesian neural networks and […]