Bayesian Nonparametrics: An invitation to Bayesian nonparametrics

By Nils Lid Hjort, Christopher C. Holmes, Peter Müller, Stephen G. Walker. 2010

60 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/24bba27870352708d14f12d9506c46ffcf156f4f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. David M. Blei
2. Matthew D. Hoffman
3. Chong Wang
4. Rajesh Ranganath
5. Qiang Liu
6. Michalis K. Titsias
7. Michael I. Jordan
8. Stephan Mandt

Citations in the corpus

• Particle gibbs with ancestor sampling (2014, background): “In Bayesian nonparametrics (Hjort et al., 2010) the latent random variables of the classical Bayesian model are replaced by latent stochastic processes, which are typically non-Markovian.”
• Stochastic variational inference (2012, methodology): “Bayesian nonpara-metrics gives us a collection of flexible models—mixture models, mixed-membership models, factor models, and models with more complex structure—which grow and expand with data (Hjort et al., 2010).”