Fourth Conference on Causal Learning and Reasoning

The Fourth Conference on Causal Learning and Reasoning (CLeaR 2025) is a dedicated forum for research at the intersection of causal inference, machine learning, and reasoning, addressing one of the most fundamental challenges in AI: understanding cause and effect rather than merely detecting statistical associations. Topics include causal discovery algorithms, structural causal models, interventional and counterfactual reasoning, causal representation learning, and the application of causal methods to fairness, robustness, and scientific discovery.

CLeaR attracts machine learning researchers, statisticians, epidemiologists, and AI safety researchers who recognize that correlation-based models are insufficient for reliable decision-making in high-stakes domains. The conference plays an important role in building bridges between the theoretical causal inference community and the deep learning community, fostering collaborations that are producing new generations of causally informed models capable of reasoning about interventions and hypotheticals rather than merely interpolating past observations.