Active Manifolds: A non-linear analogue to Active Subspaces. - Robert A. Bridges; Anthony D. Gruber; Christopher Felder; Miki E. Verma; Chelsey Hoff (ICML, 2019)

P-Willmore flow with quasi-conformal mesh regularization. - Anthony D. Gruber; Eugenio Aulisa (CoRR, 2019)

Computational p-Willmore Flow with Conformal Penalty. - Anthony D. Gruber; Eugenio Aulisa (ACM Trans. Graph., 2020)

Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Yuankai Teng; Zhu Wang 003 (CoRR, 2021)

A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (CoRR, 2021)

Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation. - Yuankai Teng; Zhu Wang 003; Lili Ju; Anthony D. Gruber; Guannan Zhang (CoRR, 2021)

Energetically Consistent Model Reduction for Metriplectic Systems. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (CoRR, 2022)

A Multifidelity Monte Carlo Method for Realistic Computational Budgets. - Anthony D. Gruber; Max D. Gunzburger; Lili Ju; Zhu Wang 003 (J. Sci. Comput., 2023)

Level Set Learning with Pseudoreversible Neural Networks for Nonlinear Dimension Reduction in Function Approximation. - Yuankai Teng; Zhu Wang 003; Lili Ju; Anthony D. Gruber; Guannan Zhang (SIAM J. Sci. Comput., 2023)