2 papers
cs.LG2025
The False Promise of Zero-Shot Super-Resolution in Machine-Learned Operators
Mansi Sakarvadia, Kareem Hegazy, Amin Totounferoush +4
A core challenge in scientific machine learning, and scientific computing more generally, is modeling continuous phenomena which (in practice) are represented discretely. Machine-l…
cs.LG2025
Residuals Are Not Enough: Limits of Physics-Informed Pre-Training for Scientific Foundation Models
Amin Totounferoush, Serge Kotchourko, Michael W. Mahoney +1
Scientific foundation models (SciFMs) aim to learn generalizable representations of physical systems governed by partial differential equations (PDEs), enabling transfer across tas…