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Gibbs sampling
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#	Item
21	Learning Semantic Representations with Hidden Markov Topics Models Mark Andrews () Gabriella Vigliocco () Cognitive, Perceptual and Brain Sciences University College London, Add to Reading List Source URL: www.mjandrews.net Language: English - Date: 2014-12-16 12:40:25 Statistics Probability Machine learning Statistical natural language processing Statistical models Markov models Probability distributions Latent Dirichlet allocation Dirichlet distribution Topic model Mixture model Gibbs sampling
22	Construction of Dependent Dirichlet Processes based on Poisson Processes Dahua Lin CSAIL, MIT Add to Reading List Source URL: dahua.me Language: English - Date: 2013-01-06 22:24:50 Probability Statistics Stochastic processes Markov processes Probability distributions Poisson processes Markov models Poisson point process Poisson distribution Dirichlet process Mixture model Gibbs sampling
23	FP7-ICT Strategic Targeted Research Project (STREP) TrendMiner (NoLarge-scale, Cross-lingual Trend Mining and Summarisation of Real-time Media Streams D3.3.1 Tools for mining non-stationary data - v2 Clustering Add to Reading List Source URL: www.trendminer-project.eu Language: English - Date: 2014-05-02 17:17:44 Statistical natural language processing Machine learning Statistics Artificial intelligence Topic model Latent Dirichlet allocation Gibbs sampling Multinomial logistic regression Dynamic topic model Dirichlet-multinomial distribution
24	2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) INDEPENDENT DOUBLY ADAPTIVE REJECTION METROPOLIS SAMPLING Luca Martino? , Jesse Read† , David Luengo‡ ? Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2014-08-22 09:13:11 Statistics Monte Carlo methods Computational statistics Markov chain Monte Carlo Statistical theory Non-uniform random numbers Rejection sampling MetropolisHastings algorithm Stochastic simulation Gibbs sampling
25	Coupled Dirichlet Processes: Beyond HDP John Fisher MIT CSAIL Add to Reading List Source URL: dahua.me Language: English - Date: 2013-01-06 22:23:38 Statistics Probability Stochastic processes Hierarchical Dirichlet process Dirichlet process Dirichlet distribution Mixture model Hidden Markov model Gibbs sampling Probability distribution Poisson point process
26	Slice sampling C. Planas, and A. Rossi Joint Research Centre of European Commission MACFINROBODS WorkshopJanuary 2015, London Add to Reading List Source URL: www.macfinrobods.eu Language: English - Date: 2015-02-13 10:28:08 Statistics Statistical theory Markov chain Monte Carlo Bayesian statistics Estimation theory Monte Carlo methods Computational statistics Slice sampling Gibbs sampling Likelihood function MetropolisHastings algorithm
27	Coupling Nonparametric Mixtures via Latent Dirichlet Processes John Fisher MIT CSAIL Add to Reading List Source URL: dahua.me Language: English - Date: 2013-01-06 22:24:57 Statistics Probability Statistical natural language processing Machine learning Stochastic processes Probability distributions Dirichlet process Latent Dirichlet allocation Probabilistic latent semantic analysis Mixture model Gibbs sampling Dirichlet distribution
28	Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons Lars Buesing¤, Johannes Bill, Bernhard Nessler, Wolfgang Maass Institute for Theoretical Computer Science, Graz U Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English* - Date: 2014-10-13 19:51:17 Neuroscience Computational neuroscience Nervous system Biology Artificial neural network Biological neuron model Spiking neural network Neural oscillation Gibbs sampling Action potential Neuron Stochastic process
29	Genome Informatics 12: 83–Local Multiple Alignment of Numerical Sequences: Detection of Subtle Motifs from Protein Sequences and Add to Reading List Source URL: www.jsbi.org Language: English - Date: 2002-01-17 03:51:05 Bioinformatics Multiple sequence alignment Sequence motif Gibbs sampling Sequence Josiah Willard Gibbs Nucleic acid sequence BLAST
30	A Tensor Spectral Approach to Learning Mixed Membership Community Models arXiv:1302.2684v4 [cs.LG] 24 OctAnima Anandkumar1 , Rong Ge2 , Daniel Hsu3 , and Sham M. Kakade3 Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-10-27 21:56:48 Networks Graph theory Probability distributions Machine learning Statistical models Community structure Dirichlet distribution Higher-order singular value decomposition Stochastic block model Gibbs sampling Markov chain Tensor

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