Full Papers
Original research contributions with substantial technical depth and results.
Machine Learning/CORE Unranked
CDM 2026
UAI 2026 Workshop on Causality for Decision Making
The UAI Workshop 2026 is a venue for presenting and discussing cutting-edge research in uncertainty in artificial intelligence, co-located with the Conference on Uncertainty in Artificial Intelligence. It welcomes contributions that advance theoretical foundations, algorithms, and applications of probabilistic and uncertain reasoning in AI.
Key deadlines
Verified September 9, 2026Full paper
June 21, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
June 21, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short Papers
Preliminary results, work-in-progress, or position papers with clear insights.
Journal Track
Extended versions of previously published journal articles suitable for workshop presentation.
Research areas in scope
01
Topics of Interest
Probabilistic graphical modelsCausal inferenceUncertainty in deep learningApproximate inference methodsDecision making under uncertaintyBayesian optimizationUncertainty quantificationRobust and reliable AIApplications of uncertainty modeling in real-world domains
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Full papers are limited to 8 pages, short papers to 4 pages, excluding references.
- Dual submission to other conferences or journals is not permitted during review.
- Author lists and affiliations may be updated after acceptance.
- Authors must include a statement regarding the use of AI tools in the submission.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026