Deep Learning Advances in Uncertainty and Generative Modeling - Session 1

Attend a 2-hour oral session on deep learning from the Uncertainty in Artificial Intelligence (UAI) 2024 conference. Explore cutting-edge research presentations on topics including Bayesian deep learning, constrained generative modeling, neural visual concept composition, conformal regression with normalizing flows, and deep heteroskedastic regression. Gain insights from five talks covering functional Wasserstein bridge inference, reflected Schrödinger bridges, learning to compose visual concepts as programs, normalizing flows applications, and understanding pathologies in regression models. Access the full research papers via the provided OpenReview links to delve deeper into the methodologies, experiments, and findings presented by leading researchers in the field of deep learning and uncertainty quantification.