13 citations · 13 across the 1 of their papers we have counts for
2 papers
physics.comp-ph2019★ 13 cited
Machine learning materials physics: Deep neural networks trained on elastic free energy data from martensitic microstructures predict homogenized stress fields with high accuracy
K. Sagiyama, K. Garikipati
We present an approach to numerical homogenization of the elastic response of microstructures. Our work uses deep neural network representations trained on data obtained from direc…
physics.comp-ph2018
A graph theoretic framework for representation, exploration and analysis on computed states of physical systems
R. Banerjee, K. Sagiyama, G. H. Teichert +1
A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to the…