Athanasios Kottas

Statistics and Probability · 2001–2014

A researcher in the Science corpus: 12 papers; trusts 55 researchers and is trusted by 61 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 76 citations into it; #942 of 12,932 by trust here, #2,108 by citations
• Artificial Intelligence — 58 citations into it; #2,712 of 35,345 by trust here, #8,525 by citations
• Environmental Engineering — 12 citations into it; #822 of 5,479 by trust here, #2,867 by citations
• Applied Mathematics — 9 citations into it; #2,906 of 7,620 by trust here, #5,850 by citations
• Mathematical Physics — 8 citations into it
• Economics and Econometrics — 7 citations into it; #8,560 of 23,481 by trust here, #20,730 by citations
• Probabilistic & Bayesian Methods — 7 citations into it
• Finance — 6 citations into it

Whom Athanasios Kottas trusts overall

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

1. Radford M. Neal
2. Alan E. Gelfand
3. Matthew West
4. Thomas S. Ferguson
5. Timothy E. Hanson
6. Efthymios G. Tsionas
7. Peter Müller
8. A. Brix
9. Keming Yu
10. T. Lancaster

Who trusts Athanasios Kottas overall

1. Matt Taddy
2. David B. Dunson
3. Timothy E. Hanson
4. Keming Yu
5. Thomas Kneib
6. Surya T. Tokdar
7. Mauro Bernardi
8. Hideo Kozumi
9. Hassan Salah Hassan Bakouch
10. Abel Rodríguez

Papers from Athanasios Kottas's perspective

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

1. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems
2. Bayesian Density Estimation and Inference Using Mixtures
3. Estimating normal means with a conjugate style dirichlet process prior
4. Bayesian analysis of binary and polychotomous response data
5. Gibbs Sampling Methods for Stick-Breaking Priors
6. Markov Chain Sampling Methods for Dirichlet Process Mixture Models
7. Sampling-Based Approaches to Calculating Marginal Densities
8. Modelling Heterogeneity With and Without the Dirichlet Process
9. Marginal Likelihood and Bayes Factors for Dirichlet Process Mixture Models
10. Sequential importance sampling for nonparametric Bayes models: The next generation

Their papers

• Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis (2007) — 121 citations
• Bayesian Semiparametric Median Regression Modeling (2001) — 218 citations
• Mixture Modeling for Marked Poisson Processes (2010) — 71 citations
• A Bayesian Nonparametric Approach to Inference for Quantile Regression (2010) — 139 citations
• Bayesian Semiparametric Regression for Median Residual Life (2003) — 66 citations
• Nonparametric Bayesian Modeling for Multivariate Ordinal Data (2005) — 119 citations
• Nonparametric Bayesian survival analysis using mixtures of Weibull distributions (2006) — 105 citations
• Bayesian Semiparametric Modelling in Quantile Regression (2009) — 166 citations
• Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical Data (2009) — 49 citations
• Bayesian Nonparametric Modeling for Multivariate Ordinal Regression (2014) — 60 citations
• THE NEUTRON STAR MASS DISTRIBUTION (2010) — 249 citations
• Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing (2005) — 409 citations