Data-driven integration kernels for interpretable nonlocal operator learning
Published in Environmental Data Science, 2026
Recommended citation: Ferretti, S. L., Lin, J., Shamekh, S., Baldwin, J. W., Pritchard, M. S., and Beucler, T. (2026). Data-driven integration kernels for interpretable nonlocal operator learning. Environmental Data Science, 5, e31. https://doi.org/10.1017/eds.2026.10056
Published as part of the Climate Informatics 2026 proceedings, following the conference’s peer-review process.