Error analysis of an asymptotic preserving dynamical low-rank integrator for the multi-scale radiative transfer equation. - Zhiyan Ding; Lukas Einkemmer; Qin Li 007 (CoRR, 2019)

Mean-field limit and numerical analysis for Ensemble Kalman Inversion: linear setting. - Zhiyan Ding; Qin Li 007 (CoRR, 2019)

Error Lower Bounds of Constant Step-size Stochastic Gradient Descent. - Zhiyan Ding; Yiding Chen; Qin Li 007; Xiaojin Zhu 001 (CoRR, 2019)

Ensemble Kalman Sampling: mean-field limit and convergence analysis. - Zhiyan Ding; Qin Li 007 (CoRR, 2019)

Variance reduction for Random Coordinate Descent-Langevin Monte Carlo. - Zhiyan Ding; Qin Li 007 (NeurIPS, 2020)

Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds. - Zhiyan Ding; Qin Li 007; Jianfeng Lu 001 (CoRR, 2020)

Variance reduction for Langevin Monte Carlo in high dimensional sampling problems. - Zhiyan Ding; Qin Li 007 (CoRR, 2020)

Random Coordinate Underdamped Langevin Monte Carlo. - Zhiyan Ding; Qin Li 007; Jianfeng Lu 001; Stephen J. Wright 001 (AISTATS, 2021)

Random Coordinate Langevin Monte Carlo. - Zhiyan Ding; Qin Li 007; Jianfeng Lu 001; Stephen J. Wright 001 (COLT, 2021)

Constrained Ensemble Langevin Monte Carlo. - Zhiyan Ding; Qin Li 007 (CoRR, 2021)

On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime. - Zhiyan Ding; Shi Chen 003; Qin Li 007; Stephen J. Wright 001 (CoRR, 2021)

A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks. - Shi Chen 003; Zhiyan Ding; Qin Li 007; Stephen J. Wright 001 (CoRR, 2021)

Langevin Monte Carlo: random coordinate descent and variance reduction. - Zhiyan Ding; Qin Li 007 (J. Mach. Learn. Res., 2021)

Ensemble Kalman inversion: mean-field limit and convergence analysis. - Zhiyan Ding; Qin Li 007 (Stat. Comput., 2021)

Ensemble Kalman Sampler: Mean-field Limit and Convergence Analysis. - Zhiyan Ding; Qin Li 007 (SIAM J. Math. Anal., 2021)

Dynamical Low-Rank Integrator for the Linear Boltzmann Equation: Error Analysis in the Diffusion Limit. - Zhiyan Ding; Lukas Einkemmer; Qin Li 007 (SIAM J. Numer. Anal., 2021)

Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis. - Zhiyan Ding; Shi Chen 003; Qin Li 007; Stephen J. Wright 001 (J. Mach. Learn. Res., 2022)

Convergence of stochastic gradient descent on parameterized sphere with applications to variational Monte Carlo simulation. - Nilin Abrahamsen; Zhiyan Ding; Gil Goldshlager; Lin Lin 001 (CoRR, 2023)

On optimal bases for multiscale PDEs and Bayesian homogenization. - Shi Chen 003; Zhiyan Ding; Qin Li 007; Stephen J. Wright 001 (CoRR, 2023)

High-Frequency Limit of the Inverse Scattering Problem: Asymptotic Convergence from Inverse Helmholtz to Inverse Liouville. - Shi Chen 003; Zhiyan Ding; Qin Li 007; Leonardo Zepeda-Núñez (SIAM J. Imaging Sci., 2023)

Simultaneous estimation of multiple eigenvalues with short-depth quantum circuit on early fault-tolerant quantum computers. - Zhiyan Ding; Lin Lin 001 (Quantum, 2023)

The ESPRIT Algorithm Under High Noise: Optimal Error Scaling and Noisy Super-Resolution. - Zhiyan Ding; Ethan N. Epperly; Lin Lin 001; Ruizhe Zhang 016 (FOCS, 2024)

Bayesian sampling using interacting particles. - Shi Chen 003; Zhiyan Ding; Qin Li 007 (CoRR, 2024)

Convergence of variational Monte Carlo simulation and scale-invariant pre-training. - Nilin Abrahamsen; Zhiyan Ding; Gil Goldshlager; Lin Lin 001 (J. Comput. Phys., 2024)

Quantum Multiple Eigenvalue Gaussian filtered Search: an efficient and versatile quantum phase estimation method. - Zhiyan Ding; Haoya Li; Lin Lin 001; Hongkang Ni; Lexing Ying; Ruizhe Zhang 016 (Quantum, 2024)

Swarm-Based Gradient Descent Meets Simulated Annealing. - Zhiyan Ding; Martin Guerra; Qin Li 007; Eitan Tadmor (SIAM J. Numer. Anal., 2024)

Operator-Level Quantum Acceleration of Non-Logconcave Sampling. - Jiaqi Leng; Zhiyan Ding; Zherui Chen; Lin Lin (CoRR, 2025)