Publication

Preprint:

[5] Constrained Ensemble Langevin Monte Carlo

with Qin Li, submitted, JUQ.

[4] Random Coordinate Langevin Monte Carlo

with Qin Li, Jianfeng Lu, Stephen J. Wright, submitted, COLT2021.

[3] Langevin Monte Carlo: random coordinate descent and variance reduction

with Qin Li, submitted, JMLR.

[2] Error Lower Bounds of Constant Step-size Stochastic Gradient Descent

with Yiding Chen, Qin Li, and Xiaojin Zhu, preprint.

[1] Dynamical low-rank integrator for the linear Boltzmann equation

with Qin Li and Lukas Einkemmer, submitted, SINUM.

2021:

[5] Random Coordinate Underdamped Langevin Monte Carlo

with Qin Li, Jianfeng Lu, Stephen J. Wright, AISTATS2021, PMLR 130:2701-2709, 2021.

[4] Ensemble Kalman Sampler: mean-field limit and convergence analysis

with Qin Li, SIAM J. Math. Anal., 53(2), 1546–1578 (2021).

[3] Ensemble Kalman Inversion: mean-field limit and convergence analysis

with Qin Li, Statistics and Computing, 31, 9 (2021).

[2] On a Fractional Schrödinger equation in the presence of Harmonic potential

with Hichem Hajaiej, to appear, ERA.

[1] A local sensitivity analysis in Landau Damping for the kinetic Kuramoto equation with random inputs.

with Seung-Yeal Ha and Shi Jin, Quart. Appl. Math. 79 (2021), 229-264.

2020:

[2] Variance reduction for Random Coordinate Descent-Langevin Monte Carlo

with Qin Li, 34th Conference on Neural Information Processing Systems (NeurIPS 2020).

[1] Ensemble Kalman Inversion for nonlinear problems: weights, consistency, and variance bounds

with Qin Li, Jianfeng Lu, Foundations of Data Science (2020), doi:10.3934/fods.2020018.

2019:

[1] Random regularity of a nonlinear Landau Damping solution for the Vlasov-Poisson equations with random inputs.

with Shi Jin, Int’l J. Uncertainty Quantification, 9, 123-142, 2019.