Scale and Edge Detection with Topological Derivatives. - Guozhi Dong; Markus Grasmair; Sung Ha Kang; Otmar Scherzer (SSVM, 2013)

Infinite Dimensional Optimization Models and PDEs for Dejittering. - Guozhi Dong; Aniello Raffaele Patrone; Otmar Scherzer; Ozan Öktem (SSVM, 2015)

Nonlinear Flows for Displacement Correction and Applications in Tomography. - Guozhi Dong; Otmar Scherzer (SSVM, 2017)

Efficiency analysis of European Freight Villages: three peers for benchmarking. - Congcong Yang; Alfred Taudes; Guozhi Dong (Central Eur. J. Oper. Res., 2017)

Superconvergence of gradient recovery on deviated discretized manifolds. - Guozhi Dong; Hailong Guo (CoRR, 2019)

Quantitative Magnetic Resonance Imaging: From Fingerprinting to Integrated Physics-Based Models. - Guozhi Dong; Michael Hintermüller; Kostas Papafitsoros (SIAM J. Imaging Sci., 2019)

Optimization with learning-informed differential equation constraints and its applications. - Guozhi Dong; Michael Hintermüller; Kostas Papafitsoros (CoRR, 2020)

Discontinuous Galerkin methods for the Laplace-Beltrami operator on point cloud. - Guozhi Dong; Hailong Guo; Zuoqiang Shi (CoRR, 2020)

Parametric Polynomial Preserving Recovery on Manifolds. - Guozhi Dong; Hailong Guo (SIAM J. Sci. Comput., 2020)

A Class of Second-Order Geometric Quasilinear Hyperbolic PDEs and Their Application in Imaging. - Guozhi Dong; Michael Hintermueller; Ye Zhang (SIAM J. Imaging Sci., 2021)

Convergence Rates of First- and Higher-Order Dynamics for Solving Linear Ill-Posed Problems. - Radu Ioan Bot; Guozhi Dong; Peter Elbau; Otmar Scherzer (Found. Comput. Math., 2022)

A parallel technique for multi-objective Bayesian global optimization: Using a batch selection of probability of improvement. - Kaifeng Yang; Michael Affenzeller; Guozhi Dong (Swarm Evol. Comput., 2022)

Gradients of Acquisition Functions for Bi-objective Bayesian optimization. - Kaifeng Yang; Sixuan Liu; Michael Affenzeller; Guozhi Dong (ICNC-FSKD, 2023)

Second-order flows for computing the ground states of rotating Bose-Einstein condensates. - Haifan Chen; Guozhi Dong; Wei Liu 136; Ziqing Xie (J. Comput. Phys., 2023)

Accelerated gradient flows for large bending deformations of nonlinear plates. - Guozhi Dong; Hailong Guo; Shuo Yang (CoRR, 2024)

Second-order flows for approaching stationary points of a class of non-convex energies via convex-splitting schemes. - Haifan Chen; Guozhi Dong; José A. Iglesias 002; Wei Liu 136; Ziqing Xie (CoRR, 2024)

BDF schemes for accelerated gradient flows in projection-free approximation of nonconvex constrained variational minimization. - Guozhi Dong; Zikang Gong; Ziqing Xie; Shuo Yang (CoRR, 2024)

A Descent Algorithm for the Optimal Control of ReLU Neural Network Informed PDEs Based on Approximate Directional Derivatives. - Guozhi Dong; Michael Hintermüller; Kostas Papafitsoros (SIAM J. Optim., 2024)

Gradient enhanced ADMM algorithm for dynamic optimal transport on surfaces. - Guozhi Dong; Hailong Guo; Chengrun Jiang; Zuoqiang Shi (J. Comput. Phys., 2025)

Second-Order Flows for Approaching Stationary Points of a Class of Nonconvex Energies via Convex-Splitting Schemes. - Haifan Chen; Guozhi Dong; José A. Iglesias 002; Wei Liu 136; Ziqing Xie (SIAM J. Sci. Comput., 2025)

An FDM-sFEM scheme on time-space manifolds and its superconvergence analysis. - Chengrun Jiang; Guozhi Dong; Hailong Guo; Zuoqiang Shi (CoRR, 2025)