Forty-Second Annual Conference on Uncertainty in Artificial Intelligence

The Forty-Second Annual Conference on Uncertainty in Artificial Intelligence (UAI 2026) is one of the most technically rigorous annual gatherings in AI and machine learning, focused on the principled representation and management of uncertainty in intelligent systems. Probability theory, Bayesian inference, graphical models, and causal reasoning form the theoretical backbone of the conference, which has shaped the field for over four decades.

UAI 2026 attracts researchers in probabilistic machine learning, causal inference, decision theory, reinforcement learning under uncertainty, and approximate inference. The conference is equally home to theoretical contributions—new bounds, convergence results, identifiability proofs—and applied work demonstrating that uncertainty quantification matters in medical AI, autonomous systems, and scientific discovery. For researchers who believe that any serious AI system must handle what it does not know, UAI is the essential annual forum.