Call for Papers
We welcome all original research papers of up to 4 pages in length. This length does not include
references or any supplementary materials. Reviewers are not obliged
to read supplementary materials when reviewing the paper. Submissions
should be a single file in .pdf format using this style file. The review process is
double-blind, so please ensure that all papers are appropriately
anonymized. We reserve the right to desk-reject improperly-anonymized
papers.
This workshop is non-archival; even though all accepted papers will be available on OpenReview, there are no formally-published proceedings.
| Submission link | OpenReview |
| Submission opens | Thursday, January 4, 2024 |
| Submission deadline | Saturday, February 10, 2024 (23:59 AoE) |
| Notification date | Sunday, March 3, 2024 (23:59 AoE) |
Scope and topics
We invite all submissions on using machine learning to solve differential equations with applications in science and engineering.
Key topics include but are not limited to:
- Exploration of novel applications of deep learning techniques in scientific simulations of partial or ordinary differential equations.
- Forward and inverse problems in PDEs to equation discovery, design optimization, and beyond, to witness the diverse applications of AI in scientific pursuits.
- Explainability and interpretability of AI models in scientific contexts.
If you are not sure if your topic is suitable for the workshop, please feel free to contact any of the organizers.