Liang Hong

Artificial Intelligence · with Martin · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Liang Hong trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Maria Kalli
  2. Jim E. Griffin
  3. Stephen G. Walker

Papers from Liang Hong's perspective

Ordered by how strongly the researchers Liang Hong trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Slice sampling mixture models (Statistics and computing)
  2. Bayesian Density Estimation and Inference Using Mixtures
  3. Markov Chain Sampling Methods for Dirichlet Process Mixture Models
  4. Gibbs Sampling Methods for Stick-Breaking Priors
  5. Modelling Heterogeneity With and Without the Dirichlet Process
  6. Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
  7. Adaptive Rejection Metropolis Sampling Within Gibbs Sampling
  8. Sampling the Dirichlet Mixture Model with Slices (Communications in statistics. Simulation and computation)
  9. The Bayesian Lasso
  10. Estimating normal means with a conjugate style dirichlet process prior

Their papers