Preprints & Publications

2026

  1. ICLR 2026
    Complexity Analysis of Normalizing Constant Estimation: from Jarzynski Equality to Annealed Importance Sampling and beyond
    Wei Guo, Molei Tao, and Yongxin Chen
    In The Fourteenth International Conference on Learning Representations, 2026
    arXiv HTML Poster
  2. ICLR 2026
    Proximal Diffusion Neural Sampler
    Wei Guo*, Jaemoo Choi*, Yuchen Zhu, Molei Tao, and Yongxin Chen
    In The Fourteenth International Conference on Learning Representations, 2026
    arXiv

2025

  1. ICLR 2025
    Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling
    Wei Guo, Molei Tao, and Yongxin Chen
    In The Thirteenth International Conference on Learning Representations, 2025
    arXiv HTML Poster
  2. NeurIPS 2025
    Fast solvers for discrete diffusion models: Theory and applications of high-order algorithms
    Yinuo Ren*, Haoxuan Chen*, Yuchen Zhu*, Wei Guo*, Yongxin Chen, Grant M Rotskoff, Molei Tao, and Lexing Ying
    In The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025
    arXiv HTML Poster
  3. Preprint
    Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
    Yuchen Zhu*, Wei Guo*, Jaemoo Choi, Petr Molodyk, Bo Yuan, Molei Tao, and Yongxin Chen
    arXiv preprint arXiv:2510.08233, 2025
    arXiv Code
  4. NeurIPS 2025
    MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
    Yuchen Zhu*, Wei Guo*, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, and Molei Tao
    In The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025
    arXiv HTML Code Poster

2024

  1. Preprint
    Plug-and-Play Controllable Generation for Discrete Masked Models
    Wei Guo*, Yuchen Zhu*, Molei Tao, and Yongxin Chen
    arXiv preprint arXiv:2410.02143, 2024
    arXiv

2023

  1. Undergrad Thesis
    Theoretical Analysis of the Approximation Properties of Score-Based Generative Models
    Wei Guo
    2023
    PDF