Full Papers
Original research contributions with substantial technical depth and experimental validation.
Computer Vision/CORE Unranked
BEW 2026
Beyond Euclidean Workshop
BEW 2026 (Beyond Euclidean) is a conference focused on geometric deep learning and non-Euclidean data representations, bringing together researchers from machine learning, computer vision, and applied mathematics to explore novel architectures and methods for structured data such as graphs, manifolds, and point clouds.
Key deadlines
Verified September 9, 2026Full paper
July 2, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
July 2, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short Papers
Concise presentations of novel ideas, preliminary results, or work in progress.
Journal Track
Extended versions of previously published work suitable for journal publication.
Research areas in scope
01
Topics of Interest
Geometric deep learningGraph neural networksManifold learningPoint cloud processingNon-Euclidean optimizationTopological data analysisSymmetry and equivariance in deep learningLearning on metric spacesApplications in physics, chemistry, and biologyScalability and efficiency of non-Euclidean modelsBenchmark datasets and evaluation metrics
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.
- 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