68 citations · 105 across the 5 of their papers we have counts for
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cs.LG2019
A block-random algorithm for learning on distributed, heterogeneous data
Prakash Mohan, Marc T. Henry de Frahan, Ryan King +1
Most deep learning models are based on deep neural networks with multiple layers between input and output. The parameters defining these layers are initialized using random values…
physics.comp-ph2019★ 68 cited
Deep learning for presumed probability density function models
Marc T. Henry de Frahan, Shashank Yellapantula, Ryan King +2
In this work, we use ML techniques to develop presumed PDF models for large eddy simulations of reacting flows. The joint sub-filter PDF of mixture fraction and progress variable i…