4 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 4 cited
Accelerating Training in Artificial Neural Networks with Dynamic Mode Decomposition
Mauricio E. Tano, Gavin D. Portwood, Jean C. Ragusa
Training of deep neural networks (DNNs) frequently involves optimizing several millions or even billions of parameters. Even with modern computing architectures, the computational…
physics.comp-ph2019★ 2 cited
Acceleration of Radiation Transport Solves Using Artificial Neural Networks
Mauricio Tano, Jean Ragusa
Discontinuous Finite Element Methods (DFEM) have been widely used for solving radiation transport problems in participative and non-participative media. In the DFEM met…