(2012). A tutorial on Bayesian nonparametric models. J. Math. Psychol. 56, 1-12. doi: 10.1016/j.jmp.2011.08.004Gershman S J,Blei D M.A tutorial on Bayesian nonparametric models[J].Journal of Mathematical Psychology,2012,56(1):1-12....
Bayesian nonparametric models characterize instantaneous strategies in a competitive dynamic game Kelsey R. McDonald, William F. Broderick, Scott A. Huettel & John M. Pearson Nature Communications volume 10, Article number: 1808 (2019) Cite this article 5942 Accesses 3 Altmetric Metrics details Ab...
A survey of non-exchangeable priors for Bayesian nonparametric models. IEEE 2015 paper bib Nicholas J. Foti, Sinead Williamson A Survey on Bayesian Deep Learning. ACM Computing Surveys 2020 paper bib Hao Wang, Dit-Yan Yeung Bayesian Neural Networks: An Introduction and Survey. arXiv 2020 paper ...
Bayesian Methods A survey of non-exchangeable priors for Bayesian nonparametric models. IEEE 2015 paper bib Nicholas J. Foti, Sinead Williamson A Survey on Bayesian Deep Learning. ACL 2020 paper bib Hao Wang, Dit-Yan Yeung Bayesian Neural Networks: An Introduction and Survey. arXiv 2020 paper ...
Härdle W. 1990. Applied nonparametric regression, volume 19 of Econometric Society Monographs. Cambridge University Press. Hastie T.J. and Tibshirani R.J. 1990. Generalized Additive Models, volume 43 of Monographs on Statistics and Applied Probability. Chapman and Hall, London. ...
We derive explicit Bayesian nonparametric analysis for a species sampling model with finitely many types of Gibbs form of type $\\alpha= -1$ recently introduced in Gnedin (2009). Our results complement existing analysis under Gibbs priors of type $\\alpha \\in [0, 1)$ proposed in Lijoi ...
A. Bayesian model averaging for linear regression models. J. Am. Stat. Assoc. 92, 179–191. https://doi.org/10.2307/2291462 (1997). Article MathSciNet MATH Google Scholar Hoeting, J. A., Madigan, D., Raftery, A. E. & Volinsky, C. T. Bayesian model averaging: A tutorial. ...
The CRP can allow for data-dependent selection of parameters and functional dependence on the current partition. The primary advantage of the proposed Bayesian nonparametric IRL (BNIRL) method is that the partitioned rewards can be very simple and thus easier to learn. Complex reward functions can...
Accord.MachineLearning - Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework. DiffSharp - An automa...
Accord.MachineLearning - Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework. DiffSharp - An automa...