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Markov chain Monte Carlo
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111	Matthew Simpson Contact Information Department of Economics Iowa State University Add to Reading List Source URL: www.themattsimpson.com Language: English - Date: 2014-11-23 17:22:00 Markov models Bayesian statistics Statistical inference Bayesian inference Statistical forecasting Statistical theory Markov chain Monte Carlo Markov chain Econometrics Statistics Information Science
112	Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Department of Computer Science University of Toronto Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-03-25 03:56:45 Markov models Computational statistics Statistical theory Variational Bayesian methods Hyperparameter Bayesian inference Markov chain Monte Carlo Surrogate model Estimation theory Statistics Bayesian statistics Statistical inference
113	Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio∗ FIND . US @ ON . THE . WEB ´ Eric Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-02-01 17:03:25 Markov chain Monte Carlo Markov models Markov processes Bayesian statistics Markov chain Gibbs sampling Boltzmann machine Generative model Graphical model Statistics Statistical models Probability and statistics
114	Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models Yichuan Zhang School of Informatics University of Edinburgh Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English - Date: 2014-11-07 12:03:01 Hyperparameter Markov chain Monte Carlo Statistics Bayesian statistics Normal distribution
115	Generalized Denoising Auto-Encoders as Generative Models Yoshua Bengio, Li Yao, Guillaume Alain, and Pascal Vincent D´epartement d’informatique et recherche op´erationnelle, Universit´e de Montr´eal Abstract Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-02-24 18:37:23 Statistical inference Monte Carlo methods Markov models Maximum likelihood Metropolis–Hastings algorithm Estimator Markov chain Multivariate normal distribution Bayesian network Statistics Estimation theory M-estimators
116	A primer for data assimilation with ecological models using Markov Chain Monte Carlo (MCMC) J. M. Zobitz, A. R. Desai, D. J. P. Moore & M. A. Chadwick Add to Reading List Source URL: ccr.meteor.wisc.edu Language: English - Date: 2012-08-14 09:49:09 Monte Carlo methods Model selection Computational statistics Data assimilation Ensemble Kalman filter Deviance information criterion Least squares Ecosystem model Parameter Statistics Bayesian statistics Estimation theory
117	Modeling of physical systems underspecified by data Daniel M. Tartakovsky Department of Mechanical & Aerospace Engineering University of California, San Diego Add to Reading List Source URL: computerlectures.pnnl.gov Language: English - Date: 2010-09-27 09:26:44 Numerical analysis Stochastic processes Monte Carlo methods Differential equations Polynomial chaos Partial differential equation Markov chain Importance sampling Stochastic Statistics Mathematics Probability and statistics
118	COMPSCI 276 Homework Assignment 6 Fall 2014 Instructor: Rina Dechter Due: Wednesday November 26th, Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-11-21 15:21:01 Monte Carlo methods Gibbs sampling Importance sampling Bayesian network Posterior probability Conditional probability Sampling Information bottleneck method Markov chain Statistics Bayesian statistics Markov chain Monte Carlo
119	Sampling Techniques for Probabilistic and Deterministic Graphical models Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-11-19 16:19:36 Probability and statistics Importance sampling Markov chain Monte Carlo Gibbs sampling Bayesian network Markov chain Variance reduction Probabilistic logic Sampling Statistics Monte Carlo methods Computational statistics
120	The Markov Chain Monte Carlo Revolution Persi Diaconis∗ Abstract The use of simulation for high dimensional intractable computations has revolutionized applied mathematics. Designing, improving and understanding the ne Add to Reading List Source URL: statweb.stanford.edu Language: English - Date: 2008-08-22 18:55:55 Symbol Metropolis–Hastings algorithm Normal distribution Itō diffusion Statistics Markov chain Permutation