Work

LeMON: Learning to learn multi-operator networks

Year: 2026

Type: article

Source: Neurocomputing

DOI: 10.1016/j.neucom.2026.135522

Authors: Jingmin Sun, Zecheng Zhang, Hayden Schaeffer

Institutions: Johns Hopkins University, University of Notre Dame, University of California, Los Angeles

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: U.S. Department of Energy, Office of Science, Multidisciplinary University Research Initiative, Air Force Office of Scientific Research

Awards: G1523888516, G2509896857, G3702553074, G4516736450, FEDNEMO: PHYSICS-INFORMED AND ENERGY-AWARE FEDERATED LEARNING OF NEURAL MULTI-OPERATOR LEARNERS AS SCIENTIFIC FOUNDATION MODELS, G5930192392

OpenAlex ID: W4402706416

FWCI: 13.6

Cites: 48

Cited by: 21

Related to: 10