Neural Integration of Continuous Dynamics. - Margaret Trautner; Sai Ravela (CoRR, 2019)

Informative Ensemble Kalman Learning for Neural Structure. - Margaret Trautner; Gabriel B. Margolis; Sai Ravela (DDDAS, 2020)

Informative Neural Ensemble Kalman Learning. - Margaret Trautner; Gabriel B. Margolis; Sai Ravela (CoRR, 2020)

Learn Like The Pro: Norms from Theory to Size Neural Computation. - Margaret Trautner; Ziwei Li; Sai Ravela (CoRR, 2021)

Learning Markovian Homogenized Models in Viscoelasticity. - Kaushik Bhattacharya; Burigede Liu; Andrew M. Stuart; Margaret Trautner (Multiscale Model. Simul., 2023)

An operator learning perspective on parameter-to-observable maps. - Daniel Zhengyu Huang; Nicholas H. Nelsen; Margaret Trautner (CoRR, 2024)

Discretization Error of Fourier Neural Operators. - Samuel Lanthaler; Andrew M. Stuart; Margaret Trautner (CoRR, 2024)

Learning Homogenization for Elliptic Operators. - Kaushik Bhattacharya; Nikola B. Kovachki; Aakila Rajan; Andrew M. Stuart; Margaret Trautner (SIAM J. Numer. Anal., 2024)

Learning Memory and Material Dependent Constitutive Laws. - Kaushik Bhattacharya; Lianghao Cao; George Stepaniants; Andrew M. Stuart; Margaret Trautner (CoRR, 2025)

Theory-to-Practice Gap for Neural Networks and Neural Operators. - Philipp Grohs; Samuel Lanthaler; Margaret Trautner (CoRR, 2025)