Guanyang Wang   王冠扬

Guanyang Wang Assistant Professor Department of Statistics Rutgers University, New Brunswick Contact Department of Statistics Office 453, Hill Center 110 Frelinghuysen Road Piscataway, NJ 08854 Email: guanyang.wang [at] rutgers [dot] edu

About me

Welcome! I am an assistant professor in the Department of Statistics at Rutgers University, New Brunswick.

My research primarily focuses on Monte Carlo methods, generative AI, quantum computing, and probability. Feel free to reach out if you would like to discuss our shared interests. I particularly encourage students with a strong programming background to get in touch.

My research is partially supported by NSF DMS-2210849, NSF FET-2403007, and an Adobe Data Science Research Award. Thank you!

I received my Ph.D. in Mathematics (Ph.D. minor in Statistics) from Stanford University in August 2020, advised by Prof. Persi Diaconis. Prior to that, I received my B.S. with Honors in Mathematics from University of Science and Technology of China (USTC) in Jun 2015.

With several friends and colleagues, we organize a weekly online seminar on Monte Carlo methods. Check out our recorded videos here!

My Erdős number is 2 ( [1] , [2] , and [3]. )

People

• Yasa Syed (Statistics, fifth year Ph.D. student)

• Wei Yuan (Statistics, fourth year Ph.D. student)

• Budhaditya Halder (Statistics, fourth year Ph.D. student)

• Tianze Wang (Statistics, third year Ph.D. student)

• Yuchen Wei (Mathematics, sixth year Ph.D. student)

Recent News

• New paper CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation with Bowen Song, Liyue Shen and others is on arxiv (Feb, 2025).

• New paper Non-linear Quantum Monte Carlo with Jose Blanchet, Yassine Hamoudi and Mario Szegedy is on arxiv (Feb, 2025).

• Paper Differentially Private Range Queries with Correlated Input Perturbation with Prathamesh Dharangutte, Jie Gao , and Ruobin Gong accepted by Artificial Intelligence and Statistics (AISTATS) 2025 (Jan, 2025).

• New paper On importance sampling and independent Metropolis-Hastings with an unbounded weight function with George Deligiannidis , Pierre E. Jacob, and El Mahdi Khribch is on arxiv. (Nov, 2024)

• New paper A phase transition in sampling from Restricted Boltzmann Machines with Youngwoo Kwon, Qian Qin, and Yuchen Wei is on arxiv. (Oct, 2024)

• With Valentin De Bortoli, Yang Chen , Nianqiao Ju , Sifan Liu , Sam Power , Qian Qin , we have launched a weekly online seminar on Monte Carlo methods!(Sep, 2024)

• Our collaborative proposal (PI: Mario Szegedy , Co-PI: Jose Blanchet and myself) Quantum Monte Carlo Speed Ups for Multilevel Computations and Other Statistical Algorithms [1] [2] has been awarded a $1.19 million grant by the NSF! Excited :) (Jul 2024).

• New paper Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach with Wei Yuan is on arxiv (Jun, 2024).

• New paper When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones? with Jose Blanchet, and Peter Glynn is on arxiv (Apr, 2024).

• New paper Quadratic Speed-up in Infinite Variance Quantum Monte Carlo with Jose Blanchet and Mario Szegedy is on arxiv (Jan, 2024).

• Paper Repeated averages on graphs with Ramis Movassagh and Mario Szegedy accepted in the Annals of Applied Probability (AoAP) (Jan, 2024).

Recent Works

• 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]

• Non-linear Quantum Monte Carlo
  Jose Blanchet, Yassine Hamoudi, Mario Szegedy, Guanyang Wang^* [arXiv]

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

• 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]
  Artificial Intelligence and Statistics (AISTATS) 2025 accepted

• 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]
  Major revision, the Annals of Statistics

• 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]

Miscellaneous

• Chinese Painting Generation Using Generative Adversarial Networks
  Guanyang Wang, Ying Chen, Yuan Chen
  CS231n Course Project, 2017. [Chinese Painting Dataset]

• 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]