no code implementations • 24 Jan 2020 • Se Un Park
Our objective is to estimate the unknown compositional input from its output response through an unknown system after estimating the inverse of the original system with a training set.
no code implementations • 29 Jun 2018 • Se Un Park
We present a learning theory for the training of a linear system operator having an input compositional variable and propose a Bayesian inversion method for inferring the unknown variable from an output of a noisy linear system.
no code implementations • 26 Feb 2015 • Yu-Hui Chen, Se Un Park, Dennis Wei, Gregory Newstadt, Michael Jackson, Jeff P. Simmons, Marc De Graef, Alfred O. Hero
We discretize the domain of the forward model onto a dense grid of Euler angles and for each measured pattern we identify the most similar patterns in the dictionary.