Hierarchical Bayesian Modeling with Ensemble MCMC Bayesian Computing for Astronomical Data Analysis 2014 Eric Ford Preparation For this lab, we’ll use the Julia programming language. We strongly encourage you to use th

Source URL: astrostatistics.psu.edu

Blind restoration of blurred photographs via AR modelling and MCMC

Source URL: decsai.ugr.es

• Mathematical analysis
• Statistics
• Mathematics
• Functional analysis
• Image processing
• Signal processing
• Fourier analysis
• Statistical theory
• Convolution
• Maximum likelihood estimation
• Distribution
• Normal distribution

MCMC and the Label Switching Problem in Bayesian Mixture Modelling 1 Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modelling

Source URL: www.stats.ox.ac.uk

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching Daniel Ritchie Stanford University

Source URL: jmlr.org

An Adaptive Subsampling Approach for MCMC Inference in Large Datasets R´emi Bardenet∗, Arnaud Doucet, Chris Holmes Department of Statistics, Oxford University, UK Abstract

Source URL: jmlr.org

Pseudo Marginal MCMC Or How to do Exact Inference with Approximate Methods and Playing Russian Roulette Mark Girolami Department of Statistics

Source URL: mlss2014.hiit.fi

Hierarchical Bayesian Modeling with Ensemble MCMC

Source URL: astrostatistics.psu.edu

POSTDOC Position Calibration and evaluation of MCMC algorithms for Agriculture Life-cycle Management Laboratoire MAPMO UMR CNRS 7349 – Orléans, France 1

Source URL: www.univ-orleans.fr

MCMC for doubly-intractable distributions Iain Murray Gatsby Computational Neuroscience Unit University College London

Source URL: mlg.eng.cam.ac.uk

Journal of Machine Learning ResearchSubmitted 9/12; Revised 7/13; Published Fast MCMC Sampling for Markov Jump Processes and Extensions Vinayak Rao∗

Source URL: www.stat.purdue.edu