Research works at Rutgers

• Antithetic Noise in Diffusion Models
  Jing Jia ^**, Sifan Liu ^⟐, Bowen Song, Wei Yuan, Liyue Shen ^⟐, Guanyang Wang^⟐ [arxiv]

• CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation
  Bowen Song, Zecheng Zhang, Zhaoxu Luo, Jason Hu, Wei Yuan, Jing Jia, Zhengxu Tang , Guanyang Wang^⟐, Liyue Shen ^⟐ [arXiv]
  NeurIPS 2025

• Quantum speedup of non-linear Monte Carlo problems
  Jose Blanchet, Yassine Hamoudi, Mario Szegedy, Guanyang Wang^* [arXiv]
  NeurIPS 2025, spotlight

• On importance sampling and independent Metropolis-Hastings with an unbounded weight function
  George Deligiannidis, Pierre E. Jacob, El Mahdi Khribch , Guanyang Wang^* [arXiv]
  Submitted

• A phase transition in sampling from Restricted Boltzmann Machines
  Youngwoo Kwon, Qian Qin, Guanyang Wang^*, Yuchen Wei [arXiv]
  Submitted

• Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach
  Wei Yuan ^**, Guanyang Wang [arXiv] [Code]
  Submitted

• When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones?
  Guanyang Wang, Jose Blanchet, Peter Glynn [arXiv]
  Submitted

• Differentially Private Range Queries with Correlated Input Perturbation
  Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Guanyang Wang^* [arXiv]
  AISTATS 2025

• Quadratic Speed-up in Infinite Variance Quantum Monte Carlo
  Jose Blanchet, Mario Szegedy, Guanyang Wang^* [arXiv]
  Submitted

• Spectral gap bounds for reversible hybrid Gibbs chains
  Qian Qin, Nianqiao Ju, Guanyang Wang [arXiv]
  the Annals of Statistics , 2025, 53(4): 1613-1638.

• Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC
  Tianze Wang ^**, Guanyang Wang
  Journal of Machine Learning Research (JMLR) 2023, 24(249):1−40, 2023. [arXiv] [Code] [Slides]

• Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
  Yasa Syed^**, Guanyang Wang
  Conference version: International Conference on Machine Learning (ICML) 2023 [arXiv] [Code] [Slides]

• Spectral telescope: Convergence rate bounds for random-scan Gibbs samplers based on a hierarchical structure
  Qian Qin, Guanyang Wang^*
  the Annals of Applied Probability (AoAP) 2024, Vol 34(1B), 1319-1349. [Blog by Sam] [Slides by Qian]

• Prediction and Design of Protease Enzyme Specificity Using a Structure-Aware Graph Convolutional Network
  Changpeng Lu, Joseph H. Lubin, Vidur S. Sarma, Samuel Z. Stentz, Guanyang Wang, Sijian Wang, Sagar D. Khare
  Proceedings of the National Academy of Sciences (PNAS) 2023, 120 (39) e2303590120. [bioRxiv]

• Repeated averages on graphs
  Ramis Movassagh, Mario Szegedy, Guanyang Wang^*
  the Annals of Applied Probability (AoAP) 2024, Vol 34 (4), 3781-3819. [arXiv]

• Pattern detection in bipartite networks: a review of terminology, applications and methods
  Zachary Neal, Annabel Cadieux, Diego Garlaschelli, Nicholas J. Gotelli, Fabio Saracco, Tiziano Squartini, Shade T. Shutters, Werner Ulrich, Guanyang Wang, Giovanni Strona
  Accepted, PLOS Complex Systems . [arXiv]

• Metropolis–Hastings transition kernel couplings
  John O'Leary, Guanyang Wang^*
  Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques (AIHP), 2024, 60(2): 1101-1124. [arXiv] [Slides]

• Unbiased optimal stopping via the MUSE
  Zhengqing Zhou†, Guanyang Wang†, Jose H. Blanchet, Peter W. Glynn
  Stochastic Processes and their Applications (SPA) (2022) [arXiv] [Slides]

• On the minimax spherical designs
  Weibo Fu, Guanyang Wang^*, Jun Yan
  Random Structures & Algorithms (RS&A), 2022. [arXiv]

• Exact convergence rate analysis of the Independent Metropolis-Hastings algorithms
  Guanyang Wang
  Bernoulli (BEJ), 2022. [arXiv] [Slides]

• On the theoretical properties of exchange algorithm
  Guanyang Wang
  Bernoulli (BEJ), 2022. [arXiv]

• Comment: Discussion of 'A Gibbs sampler for a class of random convex polytopes'
  Persi Diaconis, Guanyang Wang^*
  Journal of the American Statistical Association (JASA), 2021. [Slides]

• Maximal couplings of the Metropolis-Hastings algorithm
  John O'Leary†, Guanyang Wang†, Pierre E. Jacob
  Artificial Intelligence and Statistics (AISTATS), 2021 (oral presentation, 3%). [Slides] [Code]

• Integrated Cooling (i-Cool) Textile of Heat Conduction and Sweat Transportation for Personal Perspiration Management
  Yucan Peng, Wei Li, Bofei Liu, Weiliang Jin, Joseph Schaadt, Jing Tang, Guangmin Zhou, Guanyang Wang, Jiawei Zhou, Chi Zhang, Yangying Zhu, Wenxiao Huang, Tong Wu, Kenneth Goodson, Chris Dames, Ravi Prasher, Shanhui Fan, Yi Cui.
  Nature Communications, 2021

* = alphabetical order, † = equal contribution, ** = student first author

Research works at Stanford

• A fast MCMC algorithm for the uniform sampling of binary matrices with fixed margins
  Guanyang Wang
  Electronic Journal of Statistics (EJS), 2020 [Slides] [Code]

• A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior
  Guanyang Wang

• Expectation of the largest bet size in the Labouchere system
  Yanjun Han, Guanyang Wang^*
  Electronic Communications in Probability (ECP), 2019 [Slides]

• Bayesian goodness of fit tests: a conversation for David Mumford
  Persi Diaconis, Guanyang Wang^*
  Annals of Mathematical Sciences and Applications (AMSA), 2018

* = alphabetical order