Statistical parametric mapping of brain morphology: Sensitivity is dramatically increased by using brain-extracted images as inputs. - George Fein; Bennett A. Landman; Hoang Tran; Jerome Barakos; Kirk Moon; Victoria Di Sclafani; Robert Shumway (NeuroImage, 2006)

Brain atrophy in long-term abstinent alcoholics who demonstrate impairment on a simulated gambling task. - George Fein; Bennett A. Landman; Hoang Tran; Shannon McGillivray; Peter Finn; Jerome Barakos; Kirk Moon (NeuroImage, 2006)

Long time stability of four methods for splitting the evolutionary Stokes-Darcy problem into Stokes and Darcy subproblems. - William J. Layton; Hoang Tran; Xin Xiong (J. Comput. Appl. Math., 2012)

Analysis of Long Time Stability and Errors of Two Partitioned Methods for Uncoupling Evolutionary Groundwater-Surface Water Flows. - William J. Layton; Hoang Tran; Catalin Trenchea (SIAM J. Numer. Anal., 2013)

Analysis of a Stabilized CNLF Method with Fast Slow Wave Splittings for Flow Problems. - Nan Jiang 003; Hoang Tran (Comput. Methods Appl. Math., 2015)

A Crank-Nicolson Leapfrog stabilization: Unconditional stability and two applications. - Nan Jiang 003; Michaela Kubacki; William J. Layton; Marina Moraiti; Hoang Tran (J. Comput. Appl. Math., 2015)

An Empirical Study of the Adoption of an Indoor Location-Based Service: Finding Reading Rooms. - Shang Gao 002; John Krogstie; Trond Thingstad; Hoang Tran (Int. J. Technol. Hum. Interact., 2017)

Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients. - Hoang Tran; Clayton G. Webster; Guannan Zhang (Numerische Mathematik, 2017)

Reconstruction of jointly sparse vectors via manifold optimization. - Armenak Petrosyan; Hoang Tran; Clayton G. Webster (CoRR, 2018)

Polynomial approximation via compressed sensing of high-dimensional functions on lower sets. - Abdellah Chkifa; Nick C. Dexter; Hoang Tran; Clayton G. Webster (Math. Comput., 2018)

A Weighted 𝓁1-Minimization Approach For Wavelet Reconstruction of Signals and Images. - Joseph Daws Jr.; Armenak Petrosyan; Hoang Tran; Clayton G. Webster (CoRR, 2019)

A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization. - Jiaxin Zhang 005; Hoang Tran; Dan Lu 001; Guannan Zhang (CoRR, 2020)

Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy. - Jiaxing Zhang; Hoang Tran; Guannan Zhang (CoRR, 2020)

Analysis of The Ratio of $ ell_1$ and $ ell_2$ Norms in Compressed Sensing. - Yiming Xu; Akil Narayan 001; Hoang Tran; Clayton G. Webster (CoRR, 2020)

AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient. - Hoang Tran; Guannan Zhang (CoRR, 2020)

RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. - Swagath Venkataramani; Vijayalakshmi Srinivasan; Wei Wang 333; Sanchari Sen; Jintao Zhang; Ankur Agrawal; Monodeep Kar; Shubham Jain; Alberto Mannari; Hoang Tran; Yulong Li; Eri Ogawa; et al. (ISCA, 2021)

Enabling long-range exploration in minimization of multimodal functions. - Jiaxin Zhang 005; Hoang Tran; Dan Lu 001; Guannan Zhang (UAI, 2021)

Correcting Momentum with Second-order Information. - Hoang Tran; Ashok Cutkosky (CoRR, 2021)

Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack. - Hoang Tran; Dan Lu 001; Guannan Zhang (ECCV (5), 2022)

Better SGD using Second-order Momentum. - Hoang Tran; Ashok Cutkosky (NeurIPS, 2022)

Momentum Aggregation for Private Non-convex ERM. - Hoang Tran; Ashok Cutkosky (NeurIPS, 2022)

Differentially Private Online-to-batch for Smooth Losses. - Qinzi Zhang; Hoang Tran; Ashok Cutkosky (NeurIPS, 2022)

Model Calibration of the Liquid Mercury Spallation Target using Evolutionary Neural Networks and Sparse Polynomial Expansions. - Majdi I. Radaideh; Hoang Tran; Lianshan Lin; Hao Jiang; Drew Winder; Sarma Gorti; Guannan Zhang; Justin Mach; Sarah Cousineau (CoRR, 2022)

Point Cloud Data Simulation and Modelling with Aize Workspace. - Boris Mocialov; Eirik Eythorsson; Reza Parseh; Hoang Tran; Vegard Flovik (CoRR, 2023)

Orthogonally weighted 𝓁2, 1 regularization for rank-aware joint sparse recovery: algorithm and analysis. - Armenak Petrosyan; Konstantin Pieper; Hoang Tran (CoRR, 2023)

Private Zeroth-Order Nonsmooth Nonconvex Optimization. - Qinzi Zhang; Hoang Tran; Ashok Cutkosky (ICLR, 2024)

Empirical Tests of Optimization Assumptions in Deep Learning. - Hoang Tran; Qinzi Zhang; Ashok Cutkosky (CoRR, 2024)

Agricultural Landscape Understanding At Country-Scale. - Radhika Dua; Nikita Saxena; Aditi Agarwal; Alex Wilson; Gaurav Singh; Hoang Tran; Ishan Deshpande; Amandeep Kaur; Gaurav Aggarwal; Chandan Nath; Arnab Basu; Vishal Batchu; et al. (CoRR, 2024)

HydroEcoLSTM: A Python package with graphical user interface for hydro-ecological modeling with long short-term memory neural network. - Tam V. Nguyen 003; Vinh Ngoc Tran; Hoang Tran; Doan Van Binh; Toan D. Duong; Thanh Duc Dang; Pia Ebeling (Ecol. Informatics, 2025)

Ensemble score filter with image inpainting for data assimilation in tracking surface quasi-geostrophic dynamics with partial observations. - Siming Liang; Hoang Tran; Feng Bao 005; Hristo G. Chipilski; Peter Jan van Leeuwen; Guannan Zhang (CoRR, 2025)

Convergence analysis for a nonlocal gradient descent method via directional Gaussian smoothing. - Hoang Tran; Qiang Du 001; Guannan Zhang (Comput. Optim. Appl., 2025)

Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions. - Hoang Tran; Zezhong Zhang; Feng Bao 005; Dan Lu 001; Guannan Zhang (CoRR, 2025)