82 citations · 134 across the 16 of their papers we have counts for
16 papers
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Anthony Gruber, Kookjin Lee, Nathaniel Trask
Recent works have shown that physics-inspired architectures allow the training of deep graph neural networks (GNNs) without oversmoothing. The role of these physics is unclear, how…
Canonical and Noncanonical Hamiltonian Operator Inference
Anthony Gruber, Irina Tezaur
A method for the nonintrusive and structure-preserving model reduction of canonical and noncanonical Hamiltonian systems is presented. Based on the idea of operator inference, this…
Instability of Closed -Elastic Curves in
Anthony Gruber, Alvaro Pampano, Magdalena Toda
For , we show that non-circular closed -elastic curves in exist only when , in which case they are classical elastic curves, or when $p\in(0,…
A Multifidelity Monte Carlo Method for Realistic Computational Budgets
Anthony Gruber, Max Gunzburger, Lili Ju +1
A method for the multifidelity Monte Carlo (MFMC) estimation of statistical quantities is proposed which is applicable to computational budgets of any size. Based on a sequence of…
Energetically Consistent Model Reduction for Metriplectic Systems
Anthony Gruber, Max Gunzburger, Lili Ju +1
The metriplectic formalism is useful for describing complete dynamical systems which conserve energy and produce entropy. This creates challenges for model reduction, as the elimin…
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation
Yuankai Teng, Zhu Wang, Lili Ju +2
Due to the curse of dimensionality and the limitation on training data, approximating high-dimensional functions is a very challenging task even for powerful deep neural networks.…