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New Paper Submission
Paper Title: Cloud microphysics training and aerosol inference with the Fiats deep learning library
Authors: Damian Rouson, Dan Bonachea, Zhe Bai, Baboucarr Dibba, Ethan Gutmann, Katherine Rasmussen, David Torres
Repository: SEA-ISS-2025-Cloud-microphysics-training
Repository URL: https://github.com/BerkeleyLab/SEA-ISS-2025-Cloud-microphysics-training
Submission Checklist
- The paper has been properly formatted according to the repository's guidelines.
- All co-authors have reviewed and approved the submission.
- Any necessary supporting files or data are included.
- The paper adheres to any specific licensing requirements of the repository.
- Any conflicts of interest or funding sources are disclosed.
- The submission complies with ethical guidelines and standards.
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Contact Information
Corresponding Author: Damian Rouson
Email: rouson@lbl.gov
Affiliation: Lawrence Berkeley National Laboratory
ORCID ID: 0000-0002-2344-868X