Full papers
Original research contributions with substantial technical depth and results.
Machine Learning/CORE Unranked
PriGM NeurIPS2026 2026
NeurIPS 2026 Workshop on Principles of Generative Modeling (PriGM)
PriGM@NeurIPS2026 is a workshop affiliated with NeurIPS 2026 focused on probabilistic reasoning, inference, and generative models in machine learning. It aims to bring together researchers working on foundational and applied aspects of probabilistic methods, encouraging submissions that advance theory, algorithms, or applications in this domain.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Preliminary results, novel ideas, or work in progress with clear potential.
Journal track
Extended versions of previously published work, suitable for journal submission.
Research areas in scope
01
Topics of Interest
Probabilistic modeling and inferenceGenerative modelsApproximate inferenceBayesian deep learningCausal inferenceProbabilistic programmingUncertainty quantificationLatent variable modelsScalable probabilistic methodsApplications of probabilistic models in science, healthcare, and robotics
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 venues is not allowed during review.
- Author lists and affiliations may be updated after acceptance.
- Authors must include an AI-use statement in their submissions.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026