An Introduction to Bayesian Inference via Variational Approximations
暂无分享,去创建一个
[1] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[2] C. Antoniak. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems , 1974 .
[3] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[4] Richard F. Fenno. Home Style : House Members in Their Districts , 1978 .
[5] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[6] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] G. King,et al. Unifying Political Methodology: The Likelihood Theory of Statistical Inference , 1989 .
[8] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[9] J. Sethuraman. A CONSTRUCTIVE DEFINITION OF DIRICHLET PRIORS , 1991 .
[10] D. Rubin,et al. Inference from Iterative Simulation Using Multiple Sequences , 1992 .
[11] S. Chib,et al. Bayesian analysis of binary and polychotomous response data , 1993 .
[12] Simon Jackman,et al. Bayesian Inference for Comparative Research , 1994, American Political Science Review.
[13] Bradley P. Carlin,et al. Markov Chain Monte Carlo conver-gence diagnostics: a comparative review , 1996 .
[14] M. Escobar,et al. Bayesian Density Estimation and Inference Using Mixtures , 1995 .
[15] L. Wasserman,et al. Computing Bayes Factors by Combining Simulation and Asymptotic Approximations , 1997 .
[16] A. Raftery,et al. A note on the Dirichlet process prior in Bayesian nonparametric inference with partial exchangeability , 1997 .
[17] M. F. Porter,et al. An algorithm for suffix stripping , 1997 .
[18] John Londregan,et al. Estimating Legislators' Preferred Points , 1999, Political Analysis.
[19] Charles M. Bishop. Variational principal components , 1999 .
[20] Simon Jackman,et al. Estimation and Inference via Bayesian Simulation: An Introduction to Markov Chain Monte Carlo , 2000 .
[21] Radford M. Neal. Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .
[22] Zoubin Ghahramani,et al. Propagation Algorithms for Variational Bayesian Learning , 2000, NIPS.
[23] C. Robert,et al. Computational and Inferential Difficulties with Mixture Posterior Distributions , 2000 .
[24] Geoffrey J. McLachlan,et al. Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.
[25] Mario Medvedovic,et al. Bayesian infinite mixture model based clustering of gene expression profiles , 2002, Bioinform..
[26] Alan E Gelfand,et al. A Nonparametric Bayesian Modeling Approach for Cytogenetic Dosimetry , 2002, Biometrics.
[27] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[28] Bo Wang,et al. Convergence and Asymptotic Normality of Variational Bayesian Approximations for Expon , 2004, UAI.
[29] Michael I. Jordan,et al. An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.
[30] Peter D. Hoff,et al. Modeling Dependencies in International Relations Networks , 2004, Political Analysis.
[31] Joshua D. Clinton,et al. The Statistical Analysis of Roll Call Data , 2004, American Political Science Review.
[32] George Casella,et al. Dynamic Tempered Transitions for Exploring Multimodal Posterior Distributions , 2004, Political Analysis.
[33] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[34] Ajay Jasra,et al. Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modeling , 2005 .
[35] Jeff Gill,et al. Elicited Priors for Bayesian Model Specifications in Political Science Research , 2005 .
[36] Yee Whye Teh,et al. A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation , 2006, NIPS.
[37] John D. Lafferty,et al. Dynamic topic models , 2006, ICML.
[38] Michael I. Jordan,et al. Hierarchical Dirichlet Processes , 2006 .
[39] Michael I. Jordan,et al. Variational inference for Dirichlet process mixtures , 2006 .
[40] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[41] J. Gill. Is Partial-Dimension Convergence a Problem for Inferences from MCMC Algorithms? , 2007, Political Analysis.
[42] Gary King,et al. Extracting Systematic Social Science Meaning from Text 1 , 2007 .
[43] Introduction to Variational Methods , 2008 .
[44] Stephen Ansolabehere,et al. The Strength of Issues: Using Multiple Measures to Gauge Preference Stability, Ideological Constraint, and Issue Voting , 2008, American Political Science Review.
[45] Simon Jackman,et al. Democracy as a Latent Variable , 2008 .
[46] P. Deb. Finite Mixture Models , 2008 .
[47] K. Quinn,et al. Identifying Intra-Party Voting Blocs in UK House of Commons , 2009 .
[48] Jeffrey R. Lax,et al. Gay Rights in the States: Public Opinion and Policy Responsiveness , 2009, American Political Science Review.
[49] G. Casella,et al. Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation , 2009 .
[50] Dragomir R. Radev,et al. How to Analyze Political Attention with Minimal Assumptions and Costs , 2010 .
[51] John K Kruschke,et al. Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.
[52] Christopher D. Manning,et al. Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..
[53] Justin Grimmer,et al. A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases , 2010, Political Analysis.
[54] Arthur Spirling,et al. Identifying Intraparty Voting Blocs in the U.K. House of Commons , 2010 .
[55] Andrew D. Martin,et al. MCMCpack: Markov chain Monte Carlo in R , 2011 .
[56] Emin Orhan. Dirichlet Processes , 2012 .