1. Chernoff-type Concentration of Empirical Probabilities in Relative Entropy Guo, F. Richard, and Thomas S. Richardson Mar, 2020 [Abs] [arXiv]
  2. Empirical Bayes for Large-scale Randomized Experiments: a Spectral Approach Guo, F. Richard, James McQueen, and Thomas S. Richardson Feb, 2020 [Abs] [arXiv]


  1. On Testing Marginal versus Conditional Independence Guo, F. Richard, and Thomas S. Richardson Biometrika 2020 [Abs] [arXiv] [HTML]
  2. How cognitive and reactive fear circuits optimize escape decisions in humans Song Qi, Demis Hassabis, Jiayin Sun, Guo, Fangjian, Nathaniel Daw, and Dean Mobbs Proceedings of the National Academy of Sciences (PNAS) 2018 [Abs] [HTML]
  3. Bounds of memory strength for power-law series Guo, Fangjian, Dan Yang, Zimo Yang, Zhi-Dan Zhao, and Tao Zhou Physical Review E 2017 [arXiv] [HTML]


  1. Boosting Variational Inference Guo, Fangjian, X Wang, K Fan, T Broderick, and D Dunson In NIPS Workshop on Advances in Approximate Bayesian Inference 2016 [Abs] [arXiv] [HTML] [Code]
  2. The Bayesian Echo Chamber: modeling social influence via linguistic accommodation Guo, Fangjian, Charles Blundell, Hanna Wallach, and Katherine Heller In AISTATS 2015 [arXiv] [HTML] [Code]
  3. Uncovering systematic bias in ratings across categories: a Bayesian approach Guo, Fangjian, and David Dunson In RecSys 2015 [HTML]
  4. Parallelizing MCMC with random partition trees Xiangyu Wang, Guo, Fangjian, Katherine Heller, and David Dunson In NIPS 2015 [Abs] [arXiv] [HTML] [Code]

notes and expository writings

  1. Causal Inference by using Invariant Prediction by Peters, Buhlmann and Meinshausen (2016) Guo, F. Richard 2018 [HTML] [Code]