Igor Prünster

Artificial Intelligence · 2003–2014

A researcher in the Science corpus: 11 papers; trusts 27 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 66 citations into it; #6,287 of 35,345 by trust here, #10,798 by citations
• Statistics and Probability — 50 citations into it; #3,470 of 12,932 by trust here, #3,801 by citations
• Mathematical Physics — 29 citations into it; #2,817 of 8,562 by trust here, #2,582 by citations
• Molecular Biology — 11 citations into it; #8,405 of 17,773 by trust here, #14,833 by citations
• Applied Mathematics — 10 citations into it
• Finance — 9 citations into it
• Statistical and Nonlinear Physics — 9 citations into it
• Condensed Matter Physics — 6 citations into it

Whom Igor Prünster trusts overall

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

1. Lancelot F. James
2. Jim Pitman
3. Antonio Lijoi
4. Hemant Ishwaran
5. Peter Müller
6. S. MacEachern
7. Matthew West
8. Chang Xuan Mao
9. Peter McCullagh
10. Ole E. Barndorff-Nielsen

Who trusts Igor Prünster overall

1. Antonio Lijoi
2. Lancelot F. James
3. S. Favaro
4. Harry Crane
5. Jim E. Griffin
6. Bernardo Nipoti
7. Ramsés H. Mena
8. A. Chao
9. Nicholas G. Polson
10. Fernando A. Quintana

Papers from Igor Prünster's perspective

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

1. Bayesian Density Estimation and Inference Using Mixtures
2. Gibbs Sampling Methods for Stick-Breaking Priors
3. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems
4. Estimating normal means with a conjugate style dirichlet process prior
5. Poisson-Kingman partitions
6. Combinatorial Stochastic Processes
7. Generalized weighted Chinese restaurant processes for species sampling mixture models
8. Poisson Process Partition Calculus with applications to Exchangeable models and Bayesian Nonparametrics
9. Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics
10. © Institute of Mathematical Statistics, 2004 Nonparametric Bayesian Data Analysis

Their papers

• On rates of convergence for posterior distributions in infinite-dimensional models (2007) — 85 citations
• Bayesian Nonparametric Estimation of the Probability of Discovering New Species (2007) — 196 citations
• Posterior Analysis for Normalized Random Measures with Independent Increments (2009) — 235 citations
• Normalized random measures driven by increasing additive processes (2004) — 72 citations
• Bayesian inference with dependent normalized completely random measures (2014) — 94 citations
• Conjugacy as a Distinctive Feature of the Dirichlet Process (2006) — 78 citations
• On the stick-breaking representation of normalized inverse Gaussian priors (2012) — 47 citations
• Bayesian Nonparametrics: Models beyond the Dirichlet process (2009) — 46 citations
• Bayesian non‐parametric inference for species variety with a two‐parameter Poisson–Dirichlet process prior (2009) — 108 citations
• Bayesian Nonparametric Analysis for a Generalized Dirichlet Process Prior (2005) — 47 citations
• Distributional results for means of normalized random measures with independent increments (2003) — 277 citations