From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
AeroMELD: A Linear Embedding of Aerosol Populations for Diagnostics and Latent Dynamics
Ehsan Saleh, Saba Ghaffari, Wenhan Tang +5
The paper presents AeroMELD, a linear, permutation‑invariant embedding method that compresses detailed aerosol particle populations into a low‑dimensional latent space while preser…
physics.ao-ph2025
Reconstructing the Aerosol State from Partial Observations with Generative Modeling
E. Saleh, S. Ghaffari, J. H. Curtis +4
Key aerosol properties that shape climate -- such as CCN activity, scattering and absorption, and ice nucleation efficiency -- are difficult to infer from measurements that typical…
physics.ao-ph2025
Generative Modeling of Aerosol State Representations
Ehsan Saleh, Saba Ghaffari, Jeffrey H. Curtis +4
Aerosol-cloud--radiation interactions remain among the most uncertain components of the Earth's climate system, in partdue to the high dimensionality of aerosol state representatio…