@article{coleman_lewis_smith_williams_morris_khuwaileh_2019, title={Gradient-Free Construction of Active Subspaces for Dimension Reduction in Complex Models with Applications to Neutronics}, volume={7}, ISSN={["2166-2525"]}, DOI={10.1137/16M1075119}, abstractNote={Recent developments in the field of reduced-order modeling---and, in particular, active subspace construction---have made it possible to efficiently approximate complex models by constructing low-o...}, number={1}, journal={SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION}, author={Coleman, Kayla D. and Lewis, Allison and Smith, Ralph C. and Williams, Brian and Morris, Max and Khuwaileh, Bassam}, year={2019}, pages={117–142} }
 @article{coleman_schmidt_smith_2016, title={Frequentist and Bayesian Lasso Techniques for Parameter Selection in Nonlinearly Parameterized Models}, volume={49}, ISSN={["2405-8963"]}, DOI={10.1016/j.ifacol.2016.10.201}, abstractNote={In this paper, we discuss the use of frequentist and Bayesian lasso (least absolute shrinkage and selection operator) techniques for parameter selection in nonlinearly parameterized models employed for control design. This is necessary to isolate the subset of identifiable or influential parameters, which can be uniquely calibrated from experimental data. We survey the performance of existing algorithms and present a new Bayesian lasso implementation based on the Delayed Rejection Adaptive Metropolis (DRAM) algorithm.}, number={18}, journal={IFAC PAPERSONLINE}, author={Coleman, Kayla D. and Schmidt, Kathleen and Smith, Ralph C.}, year={2016}, pages={416–421} }