Noisy Lagrangian Tracers for Filtering Random Rotating Compressible Flows. - Nan Chen 004; Andrew J. Majda; Xin T. Tong (J. Nonlinear Sci., 2015)

Ergodicity of Truncated Stochastic Navier Stokes with Deterministic Forcing and Dispersion. - Andrew J. Majda; Xin T. Tong (J. Nonlinear Sci., 2016)

Performance Analysis of Local Ensemble Kalman Filter. - Xin T. Tong (J. Nonlinear Sci., 2018)

Rigorous Analysis for Efficient Statistically Accurate Algorithms for Solving Fokker-Planck Equations in Large Dimensions. - Nan Chen 004; Andrew J. Majda; Xin T. Tong (SIAM/ASA J. Uncertain. Quantification, 2018)

Hitting Time of Stochastic Gradient Langevin Dynamics to Stationary Points: A Direct Analysis. - Xi Chen; Simon S. Du; Xin T. Tong (CoRR, 2019)

Localization for MCMC: sampling high-dimensional posterior distributions with local structure. - Matthias Morzfeld; Xin T. Tong; Youssef M. Marzouk (J. Comput. Phys., 2019)

Dimension Independent Generalization Error with Regularized Online Optimization. - Xi Chen; Qiang Liu 001; Xin T. Tong (CoRR, 2020)

Consistency analysis of bilevel data-driven learning in inverse problems. - Neil K. Chada; Claudia Schillings; Xin T. Tong; Simon Weissmann (CoRR, 2020)

On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics. - Xi Chen; Simon S. Du; Xin T. Tong (J. Mach. Learn. Res., 2020)

Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations. - Qiang Liu 001; Xin T. Tong (Stat. Comput., 2020)

Tikhonov Regularization within Ensemble Kalman Inversion. - Neil K. Chada; Andrew M. Stuart; Xin T. Tong (SIAM J. Numer. Anal., 2020)

MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure. - Xin T. Tong; Matthias Morzfeld; Youssef M. Marzouk (SIAM J. Sci. Comput., 2020)

Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. - Simon Weissmann; Neil K. Chada; Claudia Schillings; Xin T. Tong (CoRR, 2021)

Replica Exchange for Non-Convex Optimization. - Jing Dong; Xin T. Tong (J. Mach. Learn. Res., 2021)

Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. - Ruqi Zhang; Qiang Liu 001; Xin T. Tong (NeurIPS, 2022)

Localization in Ensemble Kalman inversion. - Xin T. Tong; Matthias Morzfeld (CoRR, 2022)

Stochastic Gradient Descent with Dependent Data for Offline Reinforcement Learning. - Jing Dong; Xin T. Tong (CoRR, 2022)

Can We Do Better Than Random Start? The Power of Data Outsourcing. - Yi Chen; Jing Dong; Xin T. Tong (CoRR, 2022)

Convergence acceleration of ensemble Kalman inversion in nonlinear settings. - Neil K. Chada; Xin T. Tong (Math. Comput., 2022)

The MMO Economist: AI Empowers Robust, Healthy, and Sustainable P2W MMO Economies. - Shiwei Zhao; Xi Yuan; Runze Wu 001; Zhipeng Hu; Haoyu Liu; Kai Wang 064; Yujing Hu; Tangjie Lv; Changjie Fan; Xin T. Tong; Jiangze Han; Yan Zheng 002; et al. (WWW (Companion Volume), 2024)

The Ensemble Kalman Filter for Dynamic Inverse Problems. - Simon Weissmann; Neil K. Chada; Xin T. Tong (CoRR, 2024)

Wasserstein gradient flow for optimal probability measure decomposition. - Jiangze Han; Christopher Thomas Ryan; Xin T. Tong (CoRR, 2024)

Stochastic Gradient Descent with Adaptive Data. - Ethan Che; Jing Dong; Xin T. Tong (CoRR, 2024)

Estimate of Koopman modes and eigenvalues with Kalman Filter. - Ningxin Liu; Shuigen Liu; Xin T. Tong; Lijian Jiang (CoRR, 2024)

Demystifying the Token Dynamics of Deep Selective State Space Models. - Thieu N. Vo; Tung D. Pham; Xin T. Tong; Tan Minh Nguyen (CoRR, 2024)

Demystifying the Token Dynamics of Deep Selective State Space Models. - Thieu N. Vo; Duy-Tung Pham; Xin T. Tong; Tan Minh Nguyen (ICLR, 2025)

Dropout Ensemble Kalman Inversion for High Dimensional Inverse Problems. - Shuigen Liu; Sebastian Reich; Xin T. Tong (SIAM J. Numer. Anal., 2025)

Local MALA-within-Gibbs for Bayesian Image Deblurring with Total Variation Prior. - Rafael Flock; Shuigen Liu; Yiqiu Dong; Xin T. Tong (SIAM J. Sci. Comput., 2025)

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces. - Yang Lyu; Yuchun Qian; Tan Minh Nguyen; Xin T. Tong (CoRR, 2025)

Localized Diffusion Models for High Dimensional Distributions Generation. - Georg A. Gottwald; Shuigen Liu; Youssef Marzouk 001; Sebastian Reich; Xin T. Tong (CoRR, 2025)

Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling. - Bihan Xu; Shiwei Zhao; Runze Wu 001; Zhenya Huang; Jiawei Wang; Zhipeng Hu; Kai Wang 064; Haoyu Liu; Tangjie Lv; Le Li; Changjie Fan; Xin T. Tong; et al. (CoRR, 2025)