68 citations · 117 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
Data recovery in computational fluid dynamics through deep image priors
Marc T. Henry de Frahan, Ray W. Grout
One of the challenges encountered by computational simulations at exascale is the reliability of simulations in the face of hardware and software faults. These faults, expected to…
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…