Research

Journal Papers

• *D. Z. Huang, N. H. Nelsen, and M. Trautner. "An operator learning perspective on parameter-to-observable maps." Foundations of Data Science. 2024. (publication) (arxiv) 

• *K. Bhattacharya, N. Kovachki, A. Rajan, A. M. Stuart, and M. Trautner. "Learning Homogenization for Elliptic Operators." SIAM Journal on Numerical Analysis. 2024. (publication) (arxiv)  

• B. Liu, E. Ocegueda, M. Trautner, A. M. Stuart, and K. Bhattacharya. "Learning Macroscopic Internal Variables and History Dependence from Microscopic Models." Journal of the Mechanics and Physics of Solids. 2023.

• *K. Bhattacharya, B. Liu, A. Stuart, and M. Trautner. "Learning Homogenized Markovian Models in Viscoelasticity." SIAM Multiscale Modeling & Simulation. 2023. 

*denotes alphabetical order

Conference Papers

• M. Trautner, G. Margolis, and S. Ravela, "Informative Neural Ensemble Kalman Learning." DDDAS. 2020. (arxiv) 

Preprints

• *S. Lanthaler, A. M. Stuart, and M. Trautner. "Discretization error of Fourier neural operators." 2024. (arXiv)

*denotes alphabetical order