We invite submissions related to the following (non-exhaustive) topics that are related to optimal transport:
Optimal Transport Theory:
- OT with generalized choices of cost functions
- Study of partial differential equations and Wasserstein gradient flows (theory + applications)
- Limits of regularization schemes
Generalizations of Optimal Transport:
- Unbalanced formulation (OT between measures of different mass)
- Gromov-Wasserstein formulation (OT with rigid transformations)
- Multi-marginal OT
- Martingale OT (financial applications, etc)
Computational and Statistical Optimal Transport
- Estimation of Monge maps, couplings, etc.
- Finite-sample convergence guarantees
- Limit distribution theory
- Study of complexity of OT algorithms
Optimal Transport for Machine Learning and Applications:
- OT costs as a loss (e.g. GANs, minimization of Wasserstein distance between empirical and population measures)
- OT to define data transformations (domain adaptation, clustering)
- High-dimensional applications such as Natural Language Processing, computational biology, vision tasks, etc.
- Low-dimensional applications such as graphics, shapes, imaging, etc.
- Submission Deadline: Oct 3rd, 2023
- Acceptance Notification: October 27th, 2023
To ensure your submission is considered, please adhere to the following guidelines:
- Formatting Instructions: Use the following style files when preparing your submission. Use the following style files when preparing your submission. Papers need to be prepared and submitted as a single file: We accept long (8 pages) and short (4 pages), with unlimited pages for references and appendix in both cases. The maximum size of submissions is 50 MB. While your submission can contain a supplement or appendix, please note that reviewers are not obliged to review supplementary material.
- Reviews: The review process will be double-blind. All submissions must be anonymized and the leakage of any identification information is prohibited.
We are soliciting submissions of original research at the interface between optimal transport theory, statistics, optimization, machine learning and applications. Authors can submit work that overlaps with previously published or submitted work, as long as it adds a new perspective on that work. Selected submissions will be presented in spotlight talks.
Note that the workshop will not have proceedings and any work that has been or will be submitted to a reviewed Machine learning conference is not considered double submission.
To submit your work, please visit the OpenReview submission website. The list of accepted papers will be posted on the workshop website.
If you have any questions, please do not hesitate to contact us at email@example.com.