Hoang A Tran Staff Mathematician Contact tranha@ornl.gov | 865.574.1283 All Publications Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning Final Report on Field Work Proposal ERKJ358: Black-Box Training for Scientific Machine Learning Models Analysis of sparse recovery for Legendre expansions using envelope bound... Model calibration of the liquid mercury spallation target using evolutionary neural networks and sparse polynomial expansions... A dictionary learning algorithm for compression and reconstruction of streaming data in preset order... Analysis of the ratio of ℓ1 and ℓ2 norms in compressed sensing... Enabling Long-range Exploration in Minimization of Multimodal Functions... Application of Machine Learning to Predict the Response of the Liquid Mercury Target at the Spallation Neutron Source... On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals... Boosting black-box adversarial attack via exploiting loss smoothness... A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations... Data-driven high-fidelity 2D microstructure reconstruction via non-local patch-based image inpainting... A mixed ℓ1 regularization approach for sparse simultaneous approximation of parameterized PDEs... Reconstructing high-dimensional Hilbert-valued functions via compressed sensing... Quantifying uncertainty in the process-structure relationship for Al–Cu solidification... Reconstruction of jointly sparse vectors via manifold optimization... Exascale Data Analytics for the DOE... Analysis of Partitioned Methods for the Biot System... Analysis of a Stabilized CNLF Method with Fast Slow Wave Splittings for Flow Problems... A new Crank-Nicolson Leapfrog stabilization: Unconditional stability and two applications... A sparse-grid method for Bayesian uncertainty quantification with application to large eddy simulation turbulence models... A convergence analysis of stochastic collocation method for Navier-Stokes equations with random input data... THE LOSS OF ACCURACY OF STOCHASTIC COLLOCATION METHOD IN SOLVING NONLINEAR DIFFERENTIAL EQUATIONS WITH RANDOM INPUT DATA... Key Links Curriculum Vitae ORCID Personal Website Google scholar ResearchGate Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Mathematics in Computation Section Data Analysis and Machine Learning Group
