Necessary and sufficient conditions for observability in power systems. - Giang Tran; Arman Kiani; Anuradha M. Annaswamy; Yoav Sharon; Alexis L. Motto; Amit Chakraborty (ISGT, 2012)

Fast Diffusion Tensor Registration with Exact Reorientation and Regularization. - Junning Li; Yonggang Shi; Giang Tran; Ivo D. Dinov; Danny J. J. Wang; Arthur W. Toga (MICCAI (2), 2012)

A unifying retinex model based on non-local differential operators. - Dominique Zosso; Giang Tran; Stanley J. Osher (Computational Imaging, 2013)

Adaptively Constrained Convex Optimization for Accurate Fiber Orientation Estimation with High Order Spherical Harmonics. - Giang Tran; Yonggang Shi (MICCAI (3), 2013)

2D Empirical Transforms. Wavelets, Ridgelets, and Curvelets Revisited. - Jérôme Gilles; Giang Tran; Stanley J. Osher (SIAM J. Imaging Sci., 2014)

Fast Local Trust Region Technique for Diffusion Tensor Registration Using Exact Reorientation and Regularization. - Junning Li; Yonggang Shi; Giang Tran; Ivo D. Dinov; Danny J. J. Wang; Arthur W. Toga (IEEE Trans. Medical Imaging, 2014)

A Random Walk Model for Optimization of Search Impact in Web Frontier Ranking. - Giang Tran; Ata Turk; Berkant Barla Cambazoglu; Wolfgang Nejdl (SIGIR, 2015)

An L1 Penalty Method for General Obstacle Problems. - Giang Tran; Hayden Schaeffer; William M. Feldman; Stanley J. Osher (SIAM J. Appl. Math., 2015)

Non-Local Retinex - A Unifying Framework and Beyond. - Dominique Zosso; Giang Tran; Stanley J. Osher (SIAM J. Imaging Sci., 2015)

Fiber Orientation and Compartment Parameter Estimation From Multi-Shell Diffusion Imaging. - Giang Tran; Yonggang Shi (IEEE Trans. Medical Imaging, 2015)

Exact Recovery of Chaotic Systems from Highly Corrupted Data. - Giang Tran; Rachel A. Ward (Multiscale Model. Simul., 2017)

Recovery guarantees for polynomial approximation from dependent data with outliers. - Lam Si Tung Ho; Hayden Schaeffer; Giang Tran; Rachel A. Ward (CoRR, 2018)

Extracting Sparse High-Dimensional Dynamics from Limited Data. - Hayden Schaeffer; Giang Tran; Rachel A. Ward (SIAM J. Appl. Math., 2018)

Feature learning for representing sparse networks based on random walks. - Thanh Le 001; Giang Tran; Hoai Bac Le (Intell. Data Anal., 2020)

Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. - Lam Si Tung Ho; Hayden Schaeffer; Giang Tran; Rachel A. Ward (J. Approx. Theory, 2020)

Extracting Structured Dynamical Systems Using Sparse Optimization With Very Few Samples. - Hayden Schaeffer; Giang Tran; Rachel A. Ward; Linan Zhang (Multiscale Model. Simul., 2020)

Function Approximation via Sparse Random Features. - Abolfazl Hashemi; Hayden Schaeffer; Robert Shi; Ufuk Topcu; Giang Tran; Rachel A. Ward (CoRR, 2021)

Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data. - Lam Si Tung Ho; Giang Tran (CoRR, 2021)

HARFE: Hard-Ridge Random Feature Expansion. - Esha Saha; Hayden Schaeffer; Giang Tran (CoRR, 2022)

SRMD: Sparse Random Mode Decomposition. - Nicholas Richardson; Hayden Schaeffer; Giang Tran (CoRR, 2022)

SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics. - Esha Saha; Lam Si Tung Ho; Giang Tran (CoRR, 2022)

Diffusion Random Feature Model. - Esha Saha; Giang Tran (CoRR, 2023)

Fast Multipole Attention: A Divide-and-Conquer Attention Mechanism for Long Sequences. - Yanming Kang; Giang Tran; Hans De Sterck (CoRR, 2023)