Full Papers
Original research contributions with substantial technical depth and experimental validation.
Machine Learning/CORE Unranked
DynaFront@NeurIPS26 2026
Dynamics at the Frontiers of Optimization, Sampling, and Games
DynaFront@NeurIPS26 is a workshop affiliated with NeurIPS 2026 focused on dynamic frontiers in machine learning, particularly on adaptive, evolving, and non-stationary learning systems. It aims to bring together researchers exploring theoretical foundations, algorithms, and applications of models that evolve over time or in response to changing environments.
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 for discussion and feedback.
Journal Track
Extended versions of previously published work suitable for journal submission, with significant new analysis or results.
Research areas in scope
01
Research Topics
Adaptive and online learningNon-stationary and concept-drift learningContinual and lifelong learningDynamic graph learningTime-varying and streaming data modelingMeta-learning for dynamic environmentsReinforcement learning in changing environmentsDynamic model selection and architecture evolutionCausal inference under distribution shiftRobustness and generalization in evolving settings
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 cannot be changed after the submission deadline.
- Authors must include a statement on 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